bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncertainty quantification in multi-parametric MRI-based meningioma radiotherapy target segmentation
Authors: Wang Lana , Yang Zhenyu , LaBella Dominic , Reitman Zachary , Ginn John , Zhao Jingtong , Adamson Justus , Lafata Kyle , Calabrese Evan , Kirkpatrick John , Wang Chunhao
Published: January 2025

Purpose

This work investigates the use of a spherical projection-based U-Net (SPU-Net) segmentation model to improve meningioma segmentation performance and allow for uncertainty quantification.

Methods

A total of 76 supratentorial meningioma patients treated with radiotherapy were studied. Gross tumor volumes (GTVs) were contoured by a single experienced radiation oncologist on high-resolution contrast-enhanced T1 MRI scans (T1ce), and both T1 and T1ce images were utilized for segmentation. SPU-Net, an adaptation of U-Net incorporating spherical image projection to map 2D images onto a spherical surface, was proposed. As an equivalence of a nonlinear image transform, projections enhance locoregional details while maintaining the global field of view. By employing multiple projection centers, SPU-Net generates various GTV segmentation predictions, the variance indicating the model’s uncertainty. This uncertainty is quantified on a pixel-wise basis using entropy calculations and aggregated through Otsu’s method for a final segmentation.

Results/conclusion

The SPU-Net model poses an advantage over traditional U-Net models by providing a quantitative method of displaying segmentation uncertainty. Regarding segmentation performance, SPU-Net demonstrated comparable results to a traditional U-Net in sensitivity (0.758 vs. 0.746), Dice similarity coefficient (0.760 vs. 0.742), reduced mean Hausdorff distance (mHD) (0.612 cm vs 0.744 cm), and reduced 95% Hausdorff distance (HD95) (2.682 cm vs 2.912 cm). SPU-Net not only is comparable to U-Net in segmentation performance but also offers a significant advantage by providing uncertainty quantification. The added SPU-Net uncertainty mapping revealed low uncertainty in accurate segments (e.g., within GTV or healthy tissue) and higher uncertainty in problematic areas (e.g., GTV boundaries, dural tail), providing valuable insights for potential manual corrections. This advancement is particularly valuable given the complex extra-axial nature of meningiomas and involvement with dural tissue. The capability to quantify uncertainty makes SPU-Net a more advanced and informative tool for segmentation, without sacrificing performance.
5-deoxy-rutaecarpine protects against LPS-induced acute lung injury via inhibiting NLRP3 inflammasome-related inflammation
Authors: Luo Jinque , Li Xin , Zhang Li , Deng Meijing , Zhao Jieyang , Zhang Jinghuan , Tang Wenyu , Guo Qinghua , Wang Ling
Published: January 2025

Introduction

Acute lung injury (ALI) induced by lipopolysaccharide (LPS) is a significant medical condition characterized by severe pulmonary inflammation and tissue damage. NLRP3 inflammasome-driven inflammation is essential in ALI pathogenesis, inspiring novel therapeutic strategies that focus on NLRP3 and inflammation. In this study, we investigated the therapeutic potential of 5-deoxy-rutaecarpine (5-DR), a rutaecarpine derivative, in attenuating LPS-induced ALI.

Methods

In this study, we evaluated the effects of 5-DR treatment in mice exposed to LPS, lung tissues, bronchoalveolar lavage fluid, and serum were collected for analysis. LPS-stimulated J774A.1 mouse macrophages were used to further investigate the anti-inflammatory effects of 5-DR in vitro. Various techniques including histopathology, Western blotting, and luciferase reporter assay were employed.

Results

5-DR treatment significantly reduced lung edema, inflammatory cell infiltration in mice with LPS burden, and reduced the levels of inflammatory mediators like interleukin-1β in the mice and in LPS-stimulated J774A.1 mouse macrophages. Further western blotting analysis showed 5-DR decreased the levels of NLRP3, cleaved caspase-1, and mature IL-1β in mice and J774A.1 cells exposed to LPS. Additionally, NF-κB pathway activation significantly diminished the inhibition of the NLRP3 inflammasome by 5-DR.

Discussion

Our findings highlight the therapeutic potential of 5-DR as a promising candidate for treating LPS-induced ALI, offering insights into its underlying mechanism that targets NLRP3 inflammasome-mediated inflammation.
Development and validation of soil test crop response model for beetroot (Beta vulgaris) grown in ultisols of India
Authors: Arulmani Ramasamy , Sellamuthu Kuppayevalasu Malayappagounder , Maragatham Subramaniam , Senthil Alargarsamy , Thamaraiselvi Seenapuram Palaniswami , Malathi Palaniappan , Sridevi Govindaraja
Published: January 2025

Soil Test Crop Response (STCR), a combined plant nutrient management system that enables to develop fertilizer prescription equations for balanced crop nutrition, higher yield, profitability, and better nutrient efficiency. Field trial was carried out on Typic Haplohmult soil of Nilgiris, Tamil Nadu during 2023-2024 by Implementing an Inductive combined with a targeted yield model. Field trial includes a gradient experiment with a green viz., Chenopodium album; a test crop experiment with beetroot (Hybrid Improved Crystal) and a validation experiment with beetroot. First, the fertility gradient was ensured by the biomass yield and soil fertility. Then, test crop experiment with beet root were conducted in the same field to derive the basic parameters viz., Nutrient Requirement (NR), contribution of nutrients from fertilizers (Cf), contribution of nutrients from soil (Cs) and contribution of nutrients from the Farm Yard manure (Cfym). Using the basic parameters, fertilizer prescription equations were developed based on Integrated Plant Nutrition System and validated. We found that 0.38, 0.29, and 0.46 kg of N, P2O5, and K2O, respectively, were required for producing one quintal of beetroot tuber under the integrated approach. Readily customized of fertilizer nutrient doses was developed for varying soil test values and desired yield targets of beetroot, for both inorganic (NPK) alone and NPK + Farm Yard Manure (FYM). The model was validated in the same soil series with the achievement of 40 and 45 tonnes of beetroot ha-1 with 100.9% and 96.9% of yield achievement, respectively. The Soil analysis crop response - combined Plant Nutrition System model proved that beetroot yield can be increased by 34.74%, in relation to the generally recommended dose This inductive method could save 37, 26 and 34 kg of Nitrogen, Phosphorus and Potassium, respectively when Nitrogen, Phosphorus, Potassium fertilizers are combined with 12.5 t ha-1 FYM as per soil test and targeted yield of beetroot.
DPD-YOLO: dense pineapple fruit target detection algorithm in complex environments based on YOLOv8 combined with attention mechanism
Authors: Lin Cong , Jiang Wencheng , Zhao Weiye , Zou Lilan , Xue Zhong
Published: January 2025

With the development of deep learning technology and the widespread application of drones in the agricultural sector, the use of computer vision technology for target detection of pineapples has gradually been recognized as one of the key methods for estimating pineapple yield. When images of pineapple fields are captured by drones, the fruits are often obscured by the pineapple leaf crowns due to their appearance and planting characteristics. Additionally, the background in pineapple fields is relatively complex, and current mainstream target detection algorithms are known to perform poorly in detecting small targets under occlusion conditions in such complex backgrounds. To address these issues, an improved YOLOv8 target detection algorithm, named DPD-YOLO (Dense-Pineapple-Detection YOU Only Look Once), has been proposed for the detection of pineapples in complex environments. The DPD-YOLO model is based on YOLOv8 and introduces the attention mechanism (Coordinate Attention) to enhance the network’s ability to extract features of pineapples in complex backgrounds. Furthermore, the small target detection layer has been fused with BiFPN (Bi-directional Feature Pyramid Network) to strengthen the integration of multi-scale features and enrich the extraction of semantic features. At the same time, the original YOLOv8 detection head has been replaced by the RT-DETR detection head, which incorporates Cross-Attention and Self-Attention mechanisms that improve the model’s detection accuracy. Additionally, Focaler-IoU has been employed to improve CIoU, allowing the network to focus more on small targets. Finally, high-resolution images of the pineapple fields were captured using drones to create a dataset, and extensive experiments were conducted. The results indicate that, compared to existing mainstream target detection models, the proposed DPD-YOLO demonstrated superior detection performance for pineapples in situations where the background is complex and the targets are occluded. The mAP@0.5 reached 62.0%, representing an improvement of 6.6% over the original YOLOv8 algorithm, Precision increased by 2.7%, Recall improved by 13%, and F1-score rose by 10.3%.
Efficacy of personalized feedback in encouraging sustainable washing behavior: evidence from a pilot study in Germany
Authors: Höpfl Laura , Đula Ivan , Kiss Francisco , Walter Rebecca , Wirzberger Maria
Published: January 2025

Introduction

Reducing household energy consumption through behavioral changes is a key strategy in addressing the emissions driving the climate crisis. Behavioral changes in affluent households toward more sustainable practices can have a significant positive impact. Prior research highlighted the role of individual values and motivational factors in shaping sustainable clusters. A more personalized approach toward encouraging the resulting clusters of people to adopt more sustainable strategies seems promising. Such an approach could incorporate aligned feedback, which has been proven to be a powerful mechanism throughout learning processes.

Method

Over 9 weeks, a pilot study with 50 participants investigated the impact of different types of feedback on washing behavior. The within-subjects design included (1) a baseline condition, (2) feedback on energy consumption (kWh), and (3) feedback on monetary costs per cycle (EUR). Data collection encompassed pre- and post-condition surveys, a final comprehensive survey, and a diary-formatted table. The primary objective was to evaluate the potential for individualization. Asynchronous structured interviews were conducted at the end to explore participants' perceptions and washing behaviors.

Results

While we found effects for the feedback manipulation, we found no differences between user clusters in individual washing behaviors. Furthermore, participants qualitatively reported habitual changes, feeling more knowledgeable about the monetary impacts of specific washing programs and temperatures, and wished for a more accessible preset time function. Most participants expressed willingness to switch to a dynamic energy price if it translated to significant cost savings.

Discussion

Our findings may support the notion that individualized behavior change strategies are promising. In general, these strategies should be easily applicable, cost-effective, and promote habits to be exerted regularly. Arising methodological limitations suggest further research in this domain. From an applied perspective, our research provides valuable insights for designing products, services, and regulations by governments and companies, empowering them to develop more effective strategies for reducing energy consumption.
Narrative microstructure and macrostructure in adolescents with Down syndrome and Williams syndrome
Authors: Viejo Aitana , Fernández-Urquiza Maite , Diez-Itza Eliseo
Published: January 2025

Down syndrome (DS) and Williams syndrome (WS) are genetic neurodevelopmental disorders associated with intellectual disability, showing contrasting linguistic profiles with asymmetries in grammatical (DS weakness/WS strength) vs. pragmatic abilities (DS strength/WS weakness). The aim of the present study was to explore the linguistic profiles of 14 adolescents with DS and WS, and 14 typically developing controls (matched by chronological and verbal age) by comparing the microstructure and macrostructure of narratives and their possible dissociation. Participants watched an episode of the Tom and Jerry cartoon series and were asked to retell it. The videotaped narratives were transcribed and analyzed with the tools of the CHILDES Project and the Pragmatic Evaluation Protocol for Corpora (PREP-CORP). Microstructure was assessed by productivity at the grammatical level (number of utterances) and lexical level (number of word tokens), and complexity at the grammatical level (MLU) and lexical level (number of word types). Macrostructure was assessed by the number of story elements recalled at three levels: scenarios (global), episodes (integrated), and events (detailed). Results confirmed asymmetries in the linguistic profiles of both groups, with relative strengths of adolescents with DS in macrostructure despite relative weaknesses in microstructure. Conversely, adolescents with WS exhibited strengths in narrative microstructure, but failed to show better performance than the DS group in macrostructure. Following regression analyses, microstructure predicted macrostructure in typically developing adolescents, while no association was found between both levels in the profiles of adolescents with WS and DS, which was interpreted as an atypical dissociation.
Machine learning for the diagnosis accuracy of bipolar disorder: a systematic review and meta-analysis
Authors: Pan Yi , Wang Pushi , Xue Bowen , Liu Yanbin , Shen Xinhua , Wang Shiliang , Wang Xing
Published: January 2025

Background

Diagnosing bipolar disorder poses a challenge in clinical practice and demands a substantial time investment. With the growing utilization of artificial intelligence in mental health, researchers are endeavoring to create AI-based diagnostic models. In this context, some researchers have sought to develop machine learning models for bipolar disorder diagnosis. Nevertheless, the accuracy of these diagnoses remains a subject of controversy. Consequently, we conducted this systematic review to comprehensively assess the diagnostic value of machine learning in the context of bipolar disorder.

Methods

We searched PubMed, Embase, Cochrane, and Web of Science, with the search ending on April 1, 2023. QUADAS-2 was applied to assess the quality of the literature included. In addition, we employed a bivariate mixed-effects model for the meta-analysis.

Results

18 studies were included, covering 3152 participants, including 1858 cases of bipolar disorder. 28 machine learning models were encompassed. Sensitivity and specificity in discriminating between bipolar disorder and normal individuals were 0.88 (9.5% CI: 0.74~0.95) and 0.89 (95% CI: 0.73~0.96) respectively, and the SROC curve was 0.94(95% CI: 0.92~0.96). The sensitivity and specificity for distinguishing between bipolar disorder and depression were 0.84 (95%CI: 0.80~0.87) and 0.82 (95%CI: 0.75~0.88) respectively. The SROC curve was 0.89 (95%CI: 0.86~0.91).

Conclusions

Machine learning methods can be employed for discriminating and diagnosing bipolar disorder. However, in current research, they are predominantly utilized for binary classification tasks, limiting their progress in clinical practice. Therefore, in future studies, we anticipate the development of more multi-class classification tasks to enhance the clinical applicability of these methods.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023427290, identifier CRD42023427290.
Exploring the application of AI in the education of children with autism: a public health perspective
Authors: Lan Liu , Li Ke , Li Diao
Published: January 2025

Introduction

Autism Spectrum Disorder (ASD) presents significant challenges in social communication and interaction, critically impacting the lives of children with ASD. Traditional interventions, such as Applied Behavior Analysis (ABA) and Social Skills Training (SST), have been widely used to address social skill deficits in these children. While these methods are effective, they often require substantial resources, long-term engagement, and specialized expertise, which limit their accessibility and adaptability to diverse social contexts. Recent advancements in artificial intelligence (Al), particularly Transformer-based models, offer a novel opportunity to enhance and personalize social skills training.

Methods

This study introduces a Public Health-Driven Transformer (PHDT) model specifically designed to improve social skills in children with ASD. By integrating public health principles with state-of-the-art Al methodologies, the PHDT model creates interventions that are adaptable, accessible, and sensitive to individual needs. Leveraging multi-modal data inputs-such as text, audio, and facialcues-PHDT provides real-time social context interpretation and adaptive feedback, enabling a more naturalistic and engaging learning experience.

Results and discussion

Experimental results reveal that PHDT significantly outperforms traditional methods in fostering engagement, retention, and social skill acquisition. These findings highlight PHDT's potential to improve social competencies in children with ASD and to revolutionize access to specialized support within public health frameworks. This work underscores the transformative impact of Al-driven, public health-oriented interventions in promoting equitable access to essential developmental resources and enhancing the quality of life for children with ASD.
Global burden of burns among children and adolescents: a trend analysis from the global burden of disease study 2019
Authors: Zhu Hao , Wang Ke , Liu Xiong , Ji Jianfeng , Yang Peng , Xu Feng
Published: January 2025

Precise

This study investigates global trends in burns among children and adolescents using data from the Global Burden of Disease Study 2019. Analyzing incidence and YLD rates across 204 countries from 1990 to 2019 reveals a general decline in burn-related injuries, with age and sex influencing trends. Notably, in high-SDI regions, incidence rates initially increased before reversing. These findings highlight the need for targeted public health policies and resource allocation to reduce burn-related risks in vulnerable populations.

Background

Given the lack of long-term trend studies on global burns among children and adolescents, this study examined trends in the global burden of burns among children and adolescents.

Methods

The Global Burden of Disease (GBD) Study 2019 provided the statistical data. Sex, age, region, and SDI were used as stratification variables in the study to evaluate the prevalence of burns injuries among kids and teenagers across 204 nations and territories between 1990 and 2019. YLD rates per 100,000 people and incidence rates together with their respective average annual percentage changes (AAPC) were computed to evaluate burden trends. Furthermore, AAPC in YLD rates and incidence rates spanning various age cohorts were analyzed using the Joinpoint software.

Results

The worldwide burns incidence and YLD rates of burns among kids and teenagers exhibited a general declining trend between 1990 and 2019. Concerning the general trend in new cases, incidence rates, and YLD rates, age was positively associated. In 2019, the incidence rate for females surpassed that of males, while YLD rates for females were consistently higher than those of males. New Zealand, Czechia, and Australia rank as the top three among the 204 countries studied. Interestingly, in the high SDI range, the expected values based on incidence rates reversed after first rising with the SDI.

Conclusion

Overall, the incidence and YLD rates of burns among children and adolescents have declined globally, though significant disparities exist across age groups, sexes, regions, and countries. These findings could help guide the development of more targeted strategies to reduce the burn burden in this population.
Perspectives of health workers on the facilitators and barriers to antiretroviral therapy adherence following intensive adherence counseling in Northern Uganda
Authors: Beja Humphrey , Nakayiwa Daisy , Owachgiu Innocent Ocitti , Edek Micheal Tonny , Kobusinge Veronic , Akaki Oscar , Udho Samson
Published: January 2025

Background

In some contexts, people living with HIV (PLWH) who are virally non-suppressed and participating in an intensive adherence counseling (IAC) program have demonstrated non-adherence to antiretroviral therapy (ART) even after IAC. There is limited literature on the facilitators and barriers to ART adherence following IAC.

Objective

This study aimed to explore the perspectives of healthcare workers (HCWs) on the facilitators and barriers to ART adherence following IAC among PLWH in Northern Uganda.

Methods

This was a descriptive qualitative study conducted among HCWs at the ART clinics of the two highest-volume public health facilities in Lira District. We purposively sampled 15 study participants and conducted face-to-face in-depth interviews using an interview guide formulated based on the components of the Capability, Opportunity, and Motivation framework for Behavior change (COM-B framework). Thematic analysis was used based on the COM-B framework. In this study, the desired behavior was ART adherence following IAC. Factors that were perceived to positively affect any component of the COM-B framework were classified as facilitators and those that were perceived to negatively affect were classified as barriers.

Results

The majority of the participants were females (53%), diploma holders (40%), and nurses (40%). The perceived facilitators and barriers to ART adherence following IAC emerged as six key themes under the subdivisions of the three domains of the COM-B framework: cognitive and emotional processes, physical and practical skills, accessibility and material resources, social relationships and cultural dynamics, cognitive beliefs and aspirations, and finally, emotional and subconscious drivers. These themes were identified as either facilitators or barriers to ART adherence following IAC depending on the lenses of interpretation.

Conclusions

This study offers a multidimensional insight into the facilitators and barriers to ART adherence following IAC and how the behavior influencing ART adherence can be optimized. The results suggest that optimizing cognitive and emotional processes, physical and practical skills, accessibility and material resources, social relationships and cultural dynamics, cognitive beliefs and aspirations, and emotional and subconscious drivers during IAC and any ART adherence-related intervention could yield the best level of ART adherence among the PLWH who are virally non-suppressed and on ART.
Hypovitaminosis and its association with recurrent aphthous stomatitis: a comprehensive review of clinical correlations and diagnostic considerations
Authors: Rosa Alessio , Cianconi Giovanni , De Angelis Riccardo , Pujia Alberto Maria , Arcuri Claudio
Published: January 2025

Background

Hypovitaminosis, or vitamin deficiency, has been increasingly recognized as a potential contributing factor in the development of recurrent aphthous stomatitis (RAS), a condition characterized by the periodic formation of painful ulcers in the oral mucosa.

Materials and methods

This mini review includes a literature search on PubMed, Web of Science, and Scopus databases using keywords “hypovitaminosis AND aphthous ulcers.”

Results

There is a growing body of evidence supporting the link between various vitamin deficiencies—particularly vitamins B12, C, and folate—and the prevalence of RAS, with implications for both diagnosis and management.

Conclusion

This review aims to outline the clinical and biochemical findings associated with hypovitaminosis in individuals presenting with RAS, emphasizing the diagnostic importance of recognizing vitamin deficiencies in these patients and exploring possible therapeutic approaches.
Eating green in Copenhagen: organic consumers’ path to less meat and minimal food waste
Authors: Matthiessen Lea Ellen , Smed Sinne , Jensen Jørgen Dejgård , Średnicka-Tober Dominika , Rossi Laura , Bügel Susanne Gjedsted
Published: January 2025

Introduction

Unsustainable and unhealthy food consumption is contributing significantly to the global greenhouse gases and leads to severe health problems. The largest contributors are consumers in high-income countries, such as Denmark, with large shares of meat and high amounts of food waste.

Methods

Taking Copenhagen (the capital) as a case, we aim to explore more sustainable and healthier dietary behaviours based on the organic food share in combination with dietary composition, food waste and attitudes towards change. This mixed-method study used quantitative data from an anonymous online survey and qualitative data from semi-structured interviews. For statistical analysis, 279 adult survey participants were divided into three subgroups; “low”– with up to 25% organic food share, “medium”– 26-75% organic food share and “high”– 76-100% organic food share.

Results

This study found significant differences of food intake between the subgroups for fruits & vegetables, legumes, nuts, whole grain cereals and meat. In those food categories, the share of respondents complying with the official dietary recommendations was higher for the “high” and “medium” than for the “low” organic subgroup. At the level of public procurement, meat was reduced to provide “a room for economic manoeuvre” due to higher organic price premiums. In conclusion, in Copenhagen we observed that an increased share of organic food comes along with other sustainable dietary behaviour, both at household and public kitchen level.

Discussion

Households appear motivated by societal momentum toward more sustainable diets. The public food procurement has largely been driven by politically determined goals. Further studies are needed to better understand how food systems can support the adoption of healthier, more sustainable diets — emphasizing increased plant-based foods and reduced food waste.
Exploring the effect of play on heart rate variability as a measure of positive emotional states in pigs
Authors: Steinerová Karolína , Krause Annika , Parker Sarah E. , Seddon Yolande M.
Published: January 2025

Play behaviour has been suggested to be inherently rewarding for animals, inducing positive emotional states. The psychophysiological effect of emotions can be assessed through heart rate variability (HRV), serving as a proxy measure of sympathovagal balance. This study investigated how the performance of play influences heart rate (HR) and HRV parameters (RMSSD, SDNN) in pigs. It was hypothesized that HRV would increase during and immediately after play due to predominant vagal activation compared to baseline, indicating a positive emotional state. Gilts (n = 32, 18 and 19 weeks of age), housed in standard partly-slatted pens, were selected from two pen-level play treatments: Novelty (NOV) and Play Pen (PLP). Play treatment pigs were reared with intermittent play promotion (3x/week) from 10 weeks of age. For HRV recordings, play was promoted for 15-min in pairs of gilts within treatment, with destructible novel objects given either in the home pen (NOV, 1 m2/pig), or in an enclosed ‘playpen’ area providing extra space (PLP, 2.9 m2/ pig). HRV was measured during a play session in three consecutive periods: (i) baseline (before play bout, no play occurring), (ii) play bout (play expression), and (iii) after-play (immediately after play bout). Twenty-six gilts played at least once. Play bouts lasted between 10 and 30 s (10 s: n = 60, 20 s: n = 18, 30 s: n = 6). In 10-s bouts, compared to baseline, RMSSD was higher during play (p = 0.027) and after-play (p = 0.015), while SDNN increased during play (p ≤ 0.001) and after-play (p = 0.008) only with ambulation (pig moving forward: walking or running). HR did not differ across periods but was higher at ambulation (p = 0.003). Twenty-sec bouts followed the same relationship with only numerical differences, while HRV in 30-s bouts did not differ. Treatments did not influence HRV. Results suggest that engaging in play increases HRV, with this effect persisting into the period immediately after play. This indicates that play contributes to positive emotional states in pigs. Physical activity involved in play influences HRV. More dynamic and energetic play involving ambulation might be more rewarding for pigs. This study provides evidence for assessing positive emotions in pigs and underscores the importance of incorporating rewarding experiences into conventional farming practices.
The probable progression of Epstein-Barr virus (EBV) to chronic active EBV/reactivation weakens the immune response and stimulates Cryptococcus neoformans infection, which invariably proves fatal: a case report and review of the literature
Authors: Mishra Gargee , Sarnaik Gaurav , Samanta Joydeep , Keche Archana , Negi Sanjay Singh
Published: January 2025

We have reported here the fatal outcome of Epstein-Barr virus (EBV) infection in a 58-year-old male who had probably developed reactivation/chronic active EBV (CAEBV) which gave rise to various neurological deficits, pancytopenia, and a lower CD4 count in the patient. The decreased immune response helped Cryptococcus neoformans (C. neoformans) to manifest a disseminated infection. Although he was exclusively provided with antifungal treatment and the patient appeared to be successfully treated for cryptococcal infection, no coverage of EBV appeared detrimental as the patient died the very next day. This report highlights the need for clinical suspicion of EBV in unexplained cases of neurological manifestation, the hematological disorder of pancytopenia, a lower CD4 count, and multiorgan involvement such as pleural effusion, coarse liver echotexture, and splenomegaly.
Characterizations of cytokines and viral genomes in serum of patients with Dabie bandavirus infection
Authors: Dong Zefeng , Yuan Man , Xing Yueping , Zhang Hongkai , Shen Qiang
Published: January 2025

Background

Ten cases with Dabie bandavirus infection were identified in Suzhou City, China, from April 2023 to August 2024. All 10 cases were hospitalized patients, and three died. We detected and analyzed the cytokine concentrations and viral genomes in the serum samples of these patients to identify the possible causes of the patients’ deaths and to analyze the viral genetic characteristics.

Methods

Blood serum specimens were obtained from the 10 individuals with Dabie bandavirus infection in Suzhou City. The specific nucleic acid of Dabie bandavirus was detected using a real-time reverse transcription polymerase chain reaction assay (RT-qPCR). The cytokine concentrations in serum were detected by micro enzyme-linked immunosorbent assay (ELISA). The genomes of Dabie bandavirus were amplified using a designated primer pool. The DNA sequencing libraries were prepared using a ligation method. The sequencing process was performed using a Nanopore GridION X5 instrument. Phylogenetic trees for the L, M, and S segments of Dabie bandavirus were constructed using the maximum likelihood (ML) method in MEGA 11 software, with the bootstrap value set at 1,000.

Results

All 10 patients with Dabie bandavirus infection exhibited a severe clinical course, resulting in three fatalities. The cytokine concentrations of CCL2, GM-CSF, IFN-γ, IL-1β, IL-6, IL-8, and TNF-α were significantly elevated in the fatal patients compared with the recovered cases; all p-values for these cytokine analyses were under 0.05. The Dabie bandavirus strains identified in Suzhou belonged to three distinct genotypes: A, B, and F. The nucleotide identities for the L, M, and S segments were 95.65%–99.76%, 93.73%–99.81%, and 94.62%–99.88%, respectively. The average evolutionary rate of segment S was higher than that of segment M and segment L. The ratio of dN/dS in the membrane protein was the highest. SZ03-TXF was a recombinant strain with the location of possible breakpoints at nucleotides 795 and 1,432 in the CDS region of the L segment.

Conclusion

A recombination event was identified in SZ03-TXF strain. High viral load and cytokine storm may be associated with the case fatality of Dabie bandavirus infection. We should strengthen the monitoring of nucleotide substitutions and conduct health education for high-risk populations so as to effectively prevent and control an epidemic of the Dabie bandavirus infection in the future.
Enhanced Hybrid Deep Learning Models-Based Anomaly Detection Method for Two-Stage Binary and Multi-Class Classification of Attacks in Intrusion Detection Systems
Authors: Kamal Hesham , Mashaly Maggie
Published: January 2025

As security threats become more complex, the need for effective intrusion detection systems (IDSs) has grown. Traditional machine learning methods are limited by the need for extensive feature engineering and data preprocessing. To overcome this, we propose two enhanced hybrid deep learning models, an autoencoder–convolutional neural network (Autoencoder–CNN) and a transformer–deep neural network (Transformer–DNN). The Autoencoder reshapes network traffic data, addressing class imbalance, and the CNN performs precise classification. The transformer component extracts contextual features, which the DNN uses for accurate classification. Our approach utilizes an enhanced hybrid adaptive synthetic sampling–synthetic minority oversampling technique (ADASYN-SMOTE) for binary classification and enhanced SMOTE for multi-class classification, along with edited nearest neighbors (ENN) for further class imbalance handling. The models were designed to minimize false positives and negatives, improve real-time detection, and identify zero-day attacks. Evaluations based on the CICIDS2017 dataset showed 99.90% accuracy for Autoencoder–CNN and 99.92% for Transformer–DNN in binary classification, and 99.95% and 99.96% in multi-class classification, respectively. On the NF-BoT-IoT-v2 dataset, the Autoencoder–CNN achieved 99.98% in binary classification and 97.95% in multi-class classification, while the Transformer–DNN reached 99.98% and 97.90%, respectively. These results demonstrate the superior performance of the proposed models compared with traditional methods for handling diverse network attacks.
Optical Image Generation Through Digital Terrain Models for Autonomous Lunar Navigation
Authors: Ceresoli Michele , Silvestrini Stefano , Lavagna Michèle
Published: January 2025

In recent years, Vision-Based Navigation (VBN) techniques have emerged as a fundamental component to enable autonomous spacecraft operations, particularly in challenging environments such as planetary landings, where ground control may be limited or unavailable. Developing and testing VBN algorithms requires the availability of a large number of realistic images of the application scenario; however, these are rarely available. This paper presents a novel rendering software tool to generate accurate synthetic optical images of the lunar surface by leveraging high-resolution Digital Terrain Models (DTMs). Unlike traditional ray-tracing algorithms, the method iteratively propagates camera rays to determine their intersection with the terrain surface defined by a Digital Elevation Model (DEM). The color information is then retrieved from the corresponding Digital Orthophoto Model (DOM) through the knowledge of the ray impact points, bypassing the need for the costly computation of shadows, reflections, and refractions effects. The rendering performance is demonstrated through a comprehensive selection of images of the lunar surface under different illumination conditions and camera orientations.
Effects of Sediment Content, Flooding, and Drainage Process on Rice Growth and Leaf Physiology of Early Rice During Heading–Flowering Stage
Authors: Cai Shuo , Zhang Wenlong , Wang Bingrui , Wang Haiyuan , Guo Qiaoling , Dai Yulong , Gong Laihong , Shi Hong
Published: January 2025

In recent years, there has been a notable increase in the frequency and intensity of floods and heavy rains, which has resulted in the frequent inundation of rice-growing areas. Flooding during the heading–flowering stages of early rice can result in significant yield losses. To elucidate the response of rice to sediment content, flooding, and drainage processes and their underlying mechanisms, a pot experiment was conducted to investigate the effects of sediment contents (S1: 0, S2: 0.10 kg m−3, and S3: 0.25 kg m−3), flooding time (F1: 3 days and F2: 6 days), and drainage time (D1: 3 days and D2: 6 days) during the heading–flowering stage on the oxidation resistance and grain yield of early rice in the Poyang Lake Region. At the same time, an experimental control group (CK) was set up with no sediment, no flooding, or no drainage treatment. The results showed that the flag leaf area of S1F1D2 treatment was diminished by flooding. The relative chlorophyll content (SPAD) reached its lowest value prior to drainage. The treatment of S2F2D1 showed the greatest decrease in SPAD value of 41.57%, which was only 53.88% of that of the control treatment. The activity of superoxide dismutase (SOD), peroxidase (POD), and the content of malondialdehyde (MDA) were observed to increase during the flooding period in comparison to the control treatment. The maximum values for these parameters were recorded at 5.68, 3.09, and 1.9 times higher than those of the control treatment, respectively. However, a decrease was observed after drainage. Furthermore, the occurrence of flooding during the early rice heading–flowering stage resulted in a notable reduction in the grain number per spike and the fruiting rate, consequently leading to a considerable decline in grain yields, with a decrease ranging from 31.81% to 69.96%. The findings indicate that flooding during the heading–flowering stage resulted in a reduction in early rice grain yield yet enhanced the antioxidant capacity of the leaves. Regression analyses indicated that a prediction model for the actual yield after flooding stress at the heading–flowering stage of early rice could be constructed using SFW as the independent variable. The findings of this study provide a theoretical basis for the formulation of a scientific and reasonable drainage scheme with the objective of reducing yield loss following rice flooding in the southern rice-growing region of China.
Synergistic Effects of Exogenous Lactobacillus plantarum and Fibrolytic Enzymes on Fermentation Quality, Fiber Degradation, and In Vitro Digestibility of Napiergrass (Pennisetum purpureum) Silage
Authors: Dong Dong , Zhang Lei , Zhao Jie , Dong Zhihao , Li Junfeng , Shao Tao
Published: January 2025

This experiment aimed to evaluate the effects of exogenous L. plantarum, fibrolytic enzymes, and their combination on fermentation quality, structural carbohydrate components, and in vitro dry matter digestibility (IVDMD). The treatments included (i) no additives (control), (ii) L. plantarum (L), (iii) fibrolytic enzymes (E), and (iv) a combination of fibrolytic enzymes and L. plantarum (EL). After being fermented for 1, 3, 7, and 30 days, the silos were opened for subsequent analysis. L and EL increased the lactic acid content and decreased the pH value and NH3-N content compared to silages without the addition of L. plantarum (p < 0.05). Compared to the control, enzymes alone or combined with L. plantarum improved enzymatic hydrolysis with higher water-soluble carbohydrates being retained at the early stage of ensiling; lower contents of NDF, ADF, hemicellulose, and cellulose were observed at the end of ensiling (p < 0.05). The IVDMD was improved in E and EL silage, and the highest IVDMD was observed in E. The L silage showed no significant difference in terms of the structural carbohydrate components or IVDMD compared to the control (p > 0.05). A principal component analysis showed that L. plantarum addition did not contribute to an increase in IVDMD, whereas LA fermentation was further enhanced when EL was synergistically involved.
Influence of Body Condition Score on Reproductive Recovery in Spring and on Some Hematochemical Parameters in Sarda Breed Sheep
Authors: Luridiana Sebastiano , Ouadday Mortadha , Cosso Giovanni , Carcangiu Vincenzo , Mura Maria Consuelo
Published: January 2025

This study aimed to investigate the relationship between body condition score (BCS) and reproductive recovery in Sarda dairy breed ewes, as well as its association with some hematochemical parameters, focusing on the male effect as a method to induce out-of-season ovulation. The male effect is commonly used in sheep farming as an alternative to hormonal treatments, but its success can be influenced by factors such as BCS. In this experiment, 200 healthy lactating ewes (aged 3–5 years) were divided into four groups based on BCS (2.0, 2.5, 3.0, and 3.5). BCS was measured on a 1–5 scale by touching the amounts of muscling and fat deposition in the loin region. On 15 May, 10 rams of proven fertility were introduced, and removed 50 days later. Blood samples were collected at days 15, 30, and 50 for glucose, cholesterol, triglycerides, total protein, and albumin analysis, along with BCS evaluations. Lambing dates, fertility rates, litter size, and the time from ram introduction to lambing were recorded. The results showed that ewes with a higher BCS (3.0 and 3.5) had improved fertility rates, earlier lambing, and a better overall reproductive performance compared to ewes with a lower BCS (2.0 and 2.5). Higher BCS groups also exhibited higher levels of glucose, cholesterol, and triglycerides. The study concluded that a BCS of 3.0 is optimal for reproductive efficiency in Sarda ewes during the male effect in spring, promoting better reproductive outcomes and animal welfare without the need for hormonal treatments.
An Analysis Method of Anticipated UX Evoked by Packaging Design Using the Evaluation Grid Method: A Case of the Analysis of Packages of Boxed Flour Confections and Sunscreen
Authors: Doi Toshihisa , Nagata Aoi
Published: January 2025

When considering the chronological order of product use, package design is mainly related to forming the anticipated UX, which predicts and imagines the experience gained from interacting with the product. However, in previous research, no method has been established for specifically evaluating the anticipated UX, and there is little knowledge about the relationship between packaging design and anticipated UX. This research aimed to examine a method to investigate the anticipated UX that users gain from packaging design in an exploratory and qualitative manner. We adopted the evaluation grid method, an interview and analysis technique that can clarify the evaluation structure that people have for the target of evaluation, and examined the structure of the design elements of the packaging and the appeal and sense of expectation that can be gained from them. We selected 20 products from each of two product groups for evaluation as examples: boxed flour confections and sunscreen. Ten people participated in the grid evaluation method survey for each product, and an evaluation structure diagram was created to summarize the results for each group of products. For flour confections packaging, the focus was on whether people could imagine what the taste would be like, and for sunscreen packaging, the focus was on concepts related to the performance and effectiveness of the sunscreen. These results show that it is possible to grasp the anticipated UX based on the user’s words using the evaluation grid method. The results of this research will contribute to establishing a method for examining anticipated UX and will be useful for achieving packaging design that enhances UX. In addition, the findings of the analysis cases presented in this research can be used to improve UX in the packaging of sweets and sunscreen.
An In Vitro Comparison Study Regarding Retention Force Expressed by Thermoformed Aligners and 3D-Printed Aligners with Different Thickness and Design
Authors: Cremonini Francesca , Cappelletti Marta , Brucculeri Luca , Olivero Virginia , Lombardo Luca
Published: January 2025

Background: Retention is a critical aspect of orthodontic treatment with aligners as it counteracts vertical displacing forces and ensures greater predictability of tooth movement. The aim of this study is to evaluate and compare the retention effectiveness of 3D-printed aligners and thermoformed aligners, analyzing how margin design and thickness gradients affect retention under different occlusal conditions. Methods: Tensile tests were conducted using a Sauter TVO-A01 machine, recording the force required to displace each aligner from the models. Quantitative data on the retention force of each aligner were collected based on malocclusion type and design specifics. Results: Scalloped thermoformed aligners demonstrated significantly lower retention values (p = 0.029) compared to 3D-printed aligners with high margins with horizontal and vertical gradients. Scalloped margin aligners exhibited significantly lower retention values (p = 0.008) compared to straight margin aligners. Additionally, 3D-printed aligners with uniform thickness gradients had significantly lower retention values (p = 0.040) compared to thermoformed aligners. Conclusions: The 3D printing production process enables customizable designs tailored to the unique characteristics of each patient. High-margin 3d-printed aligners with horizontal and vertical gradients provide superior retention, particularly in complex clinical situations such as dental crowding.
Central (Hemodynamic) and Peripheral (Autonomic) Synergy During Persuasion Within a Shared Decision-Making Process
Authors: Angioletti Laura , Acconito Carlotta , Saquella Federica , Balconi Michela
Published: January 2025

This hyperscanning study explores the central (hemodynamic) and peripheral (autonomic) markers of persuasion within a shared decision-making process. Decision-making was examined through a task where two decision-makers assumed the role of Persuader (P-der) and Persuaded (P-ded), with the P-der aiming to increase group decision orientation in the P-ded. Data were collected from 14 dyads using functional near-infrared spectroscopy to measure prefrontal cortex (PFC) hemodynamic activity and collection and recording of autonomic indices including heart rate (HR) and HR variability (HRV). The analysis focused on two phases: Phase 1, where the P-der presented the scenario and enacted their persuasive strategy, and Phase 2, characterized by the P-ded’s response. The results revealed significant effects on the dissimilarity indices at the dyadic level. Compared with Phase 1, Phase 2 included higher oxygenated hemoglobin dissimilarity in the PFC, indicating greater inter-dyadic divergence during the P-ded’s response. HR dissimilarity increased when the P-ded spoke, suggesting disrupted synergy, while HRV dissimilarity was higher when the P-der spoke, potentially reflecting differences in stress regulation. These findings suggest that neurophysiological coherence varies based on persuasion phases within shared decision-making, with P-ded introducing greater dissonance in dyads synergy. Compared with single-subject approaches, dyadic analyses offer a more accurate understanding of the interpersonal nature of persuasion dynamics during decision-making.
Epimorphisms Amalgams and Po-Unitary Pomonoids
Authors: Shah Aftab Hussain , Al Subaiei Bana
Published: January 2025

This paper proves that the special pomonoid amalgam with a quasi po-unitary or almost po-unitary core U is strongly poembeddable. The techniques used to establish these results involve Isbell’s zigzag theorem and its descriptions in terms of the pomonoid dominions.