bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications
Authors: Benso Francesco , Chiorri Carlo , Ardu Eleonora , Venuti Paola , Pasqualotto Angela
Published: January 2025

The concept of modularity in neuropsychology remains a topic of significant debate, especially when considering complex, non-innate, hyper-learned, and adaptable modular systems. This paper critically examines the evolution of cognitive modularity, addressing the challenges of integrating foundational theories with recent empirical and theoretical developments. We begin by analyzing the contributions of Sternberg and Fodor, whose foundational work established the concept of specialized, encapsulated modules within cognitive processes, particularly in the domains of perception and language. Building on this, we explore Carruthers’ theory of massive modularity, which extends the modular framework to broader cognitive functions, though we reject its application to central amodal systems, which are overarching and resistant to modularization. We also evaluate recent discoveries, such as mirror neurons and the neural reuse hypothesis, and their implications for traditional modularity models. Furthermore, we investigate the dynamic interactions between the Default Mode Network (DMN), Central Executive Network (CEN), and Salience Network (SN), highlighting their roles in shifting between automatic and controlled states. This exploration refines existing theoretical models, distinguishing innate systems, genetically predisposed ones, and those hyper-learned through working memory, as exemplified by the three-level model of Moscovitch and Umiltà. We address the blurred boundary between domain-specific and domain-general systems, proposing modular versus non-modular states—indexed by automaticity and mandatoriness—as key discriminators. This systematization, supported by empirical literature and our own research, provides a more stable framework for understanding modular systems, avoiding interpretive confusion across varying levels of complexity. These insights advance both theoretical understanding and practical applications in cognitive science.
Social factors influencing behavioral intentions to vaccinate: personality traits and cues to action
Authors: Li Zeming , Sun Xinying
Published: January 2025

Objectives

This study integrates the Five-Factor Model (FFM) of personality traits with the Health Belief Model (HBM) to examine associations among personality traits, cues to action, and vaccination intentions.

Method

An online survey was conducted in April 2021, with 2,098 participants (mean age = 31.22 years, SD = 8.29) completing the study. The questionnaire assessed HBM constructs and the FFM personality traits. Spearman correlation coefficients were used to evaluate associations among ordinal variables, while Structural Equation Modeling (SEM) explored complex relationships between latent variables.

Results

The findings indicate that self-efficacy (β = 0.198) and perceived barriers (β = 0.515) exert the most significant direct positive influences on vaccination intentions. Cues to action, particularly recommendations from family members (β = 0.113) and doctors (β = 0.092), also significantly affect vaccination intentions. Notably, personality traits indirectly influence vaccination intentions through self-efficacy and perceived barriers. Furthermore, agreeableness most significantly affects family suggestions, while neuroticism strongly influences recommendations from authority figures and healthcare providers, with extraversion notably impacting suggestions from peers.

Conclusions

The study highlights the influence of personality traits on cues to action, with neuroticism linked to authority influence, extraversion to peer influence, and agreeableness to familial influence. These findings emphasize the importance of incorporating individual differences into public health policies and vaccination promotion strategies. Future research should further explore the effects of diverse personality traits and community-specific profiles on vaccination behaviors to enhance intervention effectiveness.
Specific and common therapeutic factors in psychodynamic psychotherapy for children and adolescents: an overview
Authors: Sammer-Schreckenthaler Sabine , Lagetto Gloria , Unterrainer Human-Friedrich , Gelo Omar C. G.
Published: January 2025

The effectiveness of psychodynamic psychotherapy for children and adolescents (PPCA) has been increasingly demonstrated by a growing number of meta-analyses. However, very little is still known about the therapeutic factors responsible for this effectiveness. On the one hand, some authors have suggested that PPCA works because of specific therapeutic factors. On the other hand, it has been suggested that the effectiveness of PPCA may be due to factors common to different approaches. In the present paper, we provide an overview and discuss some of the existing clinical-theoretical and empirical literature on specific and common factors of PPCA. Several specific and common factors of PPCA were identified. Regarding the former, these included clinical processes (insight; working through; remembering and reconstructing; catharsis, abreaction, and regression; and transference and countertransference) and therapeutic techniques (interpretation of transference, countertransference, dreams, defense mechanisms, and resistance; verbalization; mirroring; and free play). Regarding the latter, these included relational factors (therapeutic alliance and interaction structures), patient factors (willingness to participate, readiness for change, treatment involvement, and positive expectations and hope), therapist factors (interpersonal skills, direct influence skills, credibility, involving parents, playing ability, flexibility, and allegiance), parent and interpersonal environment factors (parental willingness to participate, treatment involvement, treatment expectations, and perceived barriers to treatment participation and therapeutic change; family dynamics; parent-therapist alliance; and social support), mentalizing (of the therapist, client, and parents), and play (symbolization, affect regulation, mental state talk, and patterns of interaction). PPCA appears to work through both specific and common factors, more likely through their synergic interaction. However, empirical support for these therapeutic factors and their mutual interaction remains sparse. Future qualitative and quantitative research should address more in detail the extent to which specific factors, common factors, or both account for the effectiveness of PPCA. Identifying empirically supported specific and common factors and their possible interaction can inform and improve clinical practice and training.
Can social adversity and mental, physical and oral multimorbidity form a syndemic? A concept and protocol paper
Authors: Joury Easter , Nakhleh Eliana , Beveridge Ed , Tracy Derek , Heidari Ellie , Shiers David , Vereeken Silke , Peckham Emily , Gilbody Simon , Das-Munshi Jayati , Fortune Farida , Aggarwal Vishal R. , Mishu Masuma , Firth Joseph , Bhui Kamaldeep
Published: January 2025

Background

Clustering mental, physical and oral conditions reduce drastically the life expectancy. These conditions are precipitated and perpetuated by adverse social, economic, environmental, political and healthcare contextual factors, and sustained through bidirectional interactions forming potentially a ‘syndemic’. No previous study has investigated such potential syndemic. Thus, the present project aimed to (i) test for syndemic interactions between social adversity (socioeconomic adversity and traumatic events) and mental, physical and oral multimorbidity using the syndemic theoretical framework; and (ii) determine whether the syndemic relationships vary by age, sex and ethnicity.

Methods

Data from three large-scale population-based databases: UK BioBank, US National Health and Nutrition Examination Survey (NHANES) and the Research with East London Adolescents Community Health Survey (RELACHS) will be analysed. Structural equation modelling (SEM) will be utilised to conceptualise syndemic factors and model complex relationships between directly observed and indirectly observed (latent) variables (syndemic constructs).

Discussion

the syndemic conceptualisation provides a valuable framework to understand health and illness, and hence to better design and deliver effective and cost-effective preventative and curative integrated (syndemic) care to improve patient and population health. Such syndemic care aims to address the social determinants of health, whilst simultaneously managing all interlocked conditions.
The experience of bodily image for patients with left ventricular assist device
Authors: Milaniak Irena , Witkowska Emilia , Cebula Marta , Tomsia Paulina , Wasilewski Grzegorz , Górkiewicz-Kot Izabela , Wiśniowska-Śmiałek Sylwia , Kaleta Michał , Wierzbicki Karol
Published: January 2025

Introduction

Mechanical Cardiac Support and Left Ventricular Assist Devices (LVAD) have been demonstrated to prolong Heart Failure patients' survival and improve their quality of life. LVAD implantation has a considerable effect on patients' body image. Patients find it hard to accept the device as an extension of their body, especially the driveline. The study aimed to examine the relationships between anxiety and depressive symptoms, acceptance of illness, beliefs about pain control, and quality of life with body image among LVAD-implanted patients.

Methods

The cross-sectional study included 54 conveniently recruited patients who completed the Body Image Scale, SF-12, Acceptance of Illness Scale, Beliefs about Pain Control Questionnaire, NRS, HADS, and demographic and clinical data. Multiple regression analyses examined the associations between the research variable.

Results

The mean Age of the participants was 59.64 (SD=9.63), and 96.3% were men. The mean scores were: Body Image Scale – 28.33 (SD=5,91); Acceptance of Illness Scale – 25.51 (SD=5.92); beliefs about pain control: internal factors – 15.85 (SD=4.96), the influence of physicians – 17.57 (SD=3.15), random events – 14.37(SD=3.32), NRS=2.80(SD=1.86), HADS anxiety – 5.33 (SD=4.12), HADS depression – 4.66 (SD=3.10), SF12MCS-45.49 (SD=6.48), SF-12PCS-41,33 (SD=6.48). The presence of anxiety and depressive symptoms and complications after LVAD significantly predicted low body image concerns.

Discussion

Healthcare professionals should be aware of challenges regarding body image faced by LVAD-implanted patients and address related factors, especially anxiety and depression.
The effect of a one-time mindfulness intervention on body and mind in healthy adolescents using multimodal measurements
Authors: Ecker Angelika , Fritsch Charlotte , Schleicher Daniel , Jacob Ricarda , Kandsperger Stephanie , Brunner Romuald , Jarvers Irina
Published: January 2025

Background

Mindfulness-based interventions can improve psychological well-being and reduce symptoms of mental burden, including among adolescents. Relationships between basic mindfulness (trait mindfulness) and the immediate effects of a single mindfulness intervention have not been thoroughly researched, especially in adolescents. In this study, we aimed to elucidate these aspects by using a multimodal approach—measuring the effect of a single mindfulness intervention on both subjective and physiological parameters.

Methods

A total of 78 healthy adolescents (12–19 years of age, 50% female) were assigned to either a mindfulness or an active control group. Before and after the interventions, subjective parameters (mood, stress, and state mindfulness) were assessed using bipolar visual analogue scales. Physiological parameters (heart rate and heart rate variability) were measured before and during the interventions. Participants also completed the Self-Compassion Scale (SCS-D) with the subscale “mindfulness” as an assessment of trait mindfulness, and the State-Trait Anxiety-Depression Inventory (STADI).

Results

Our results showed no significant interactions between time and intervention, either subjectively or physiologically. For heart rate, we found a main effect of time. For all subjective parameters, we observed a main effect of trait mindfulness. Age was a relevant factor for heart rate and state mindfulness, suggesting age effects. We also observed strong correlations between trait mindfulness, trait anxiety, and depression scores.

Conclusion

A single mindfulness intervention had no immediate observable effects in our healthy adolescent sample, and possible reasons for this finding are discussed. Nevertheless, the present data show the potential for increased resilience through mindfulness in adolescence.
Heart rate variability, a potential assessment tool for identifying anxiety, depression, and sleep disorders in elderly individuals
Authors: Liu Wenna , Wang Shutong , Gu Hanyang , Li Rong
Published: January 2025

Introduction

This study investigates how anxiety, depression, and sleep disorders impact heart rate variability (HRV) in the elderly, exploring the clinical implications of HRV changes.

Methods

We examined 355 patients (163 men, 192 women) at Xijing Hospital from July 2021 to December 2022 during health check-ups. Demographics were recorded, and emotional status was assessed using the Hamilton Anxiety Scale (HAMA) and the Hamilton Depression Scale (HAMD). The Pittsburgh Sleep Quality Scale (PSQI) evaluated sleep quality. Patients were categorized into groups A-G based on the presence of emotional states and sleep disorders. HRV indices—SDNN, SDANN, RMSSD, PNN50, LF/HF, LF, and HF—were analyzed using ANOVA and multivariate logistic regression.

Results

No statistically significant differences were observed in demographic, clinical, and lifestyle factors across the eight groups. Variables assessed included age, sex, body mass index (BMI), fasting blood glucose, glycated hemoglobin (HbA1c), blood lipids, blood pressure, heart rate, and histories of smoking and alcohol consumption. Additionally, the presence of hypertension, diabetes, coronary heart disease, marital status, income, and education level were evaluated, with all showing equivalence (P > 0.05). Significant differences in HRV indices were observed across groups, particularly in group G (patients with anxiety, depression and sleep disorders), which showed decreased HRV parameters except LF/HF, and group H (control group), which showed increased parameters, also except LF/HF (P < 0.01). Anxiety was an independent risk factor for reduced SDNN, SDANN, and LF (P ≤ 0.01), and increased LF/HF ratio (P < 0.01). Depression was linked to decreased SDNN, RMSSD, PNN50, and HF (P < 0.05). Sleep disorders independently predicted reduced PNN50 and SDANN (P < 0.01).

Conclusion

HRV indices of individuals with varying emotional states and sleep disorders exhibited varying degrees of decrease. Anxiety, depression, and sleep disorders presented a superimposed effect on HRV. SDNN, SDANN, RMSSD, PNN50, HF and LF of HRV are of great reference value in the diagnosis of emotional and sleep disorders. For elderly patients experiencing cognitive impairment, HRV is anticipated to serve as a convenient and effective tool for assessing mood and sleep disorders.
Impact of childhood trauma on cognitive function in patients with bipolar disorder
Authors: Zhang Zhiyang , Zhou Chenyu , Mao Zhen , Sun Yue , Zhao Lei , Li Tian , Wang Chuanyue , Bo Qijing
Published: January 2025

Background

Patients with bipolar disorder (BD) frequently exhibit cognitive impairments. However, the association between childhood trauma as a risk factor for BD and cognitive deficits remains ambiguous.

Objective

To investigate the relationship between childhood trauma and cognitive function among patients with BD.

Methods

The study included 90 patients with BD and 94 healthy controls (HC). Childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ), and cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The relationships between childhood trauma and cognitive function.

Results

In BD group, childhood abuse and neglect were more prevalent than in HC group. Mood stabilizer use was positively associated with language abilities, while antipsychotic use negatively impacted attention. Emotional abuse predicted impaired immediate memory, with the number of episodes and valproate dosage negatively correlating with total RBANS scores, whereas education and mood stabilizer use showed positive correlations.

Conclusions

The incidence of childhood trauma was higher among BD than HC, and different types of childhood trauma had varying effects on different aspects of cognition. These studies will deepen the understanding of the complexity of BD and support the development of more effective treatment methods.
Stigma and fear during the COVID-19 pandemic: a qualitative study on the perceptions of healthcare workers in Canada and Singapore
Authors: Fahim Christine , Yu Chou Chuen , Cooper Jeanette , Theivendrampillai Suvabna , Lee Taehoon (Tom) , Wai-Ki Lau Michelle , Marquez Christine , Tang Bernard , Mathew Mathews , Sharma Malika , Wong Eric , O'Sullivan Tracey , Low James Alvin , Straus Sharon E.
Published: January 2025

Introduction

We sought to explore healthcare providers (HCPs)' perceptions of and experiences with stigma during the COVID-19 pandemic in Canada and Singapore.

Methods

We conducted a qualitative study (May 2020–February 2021) with HCPs in Canada and Singapore and developed a semi-structured interview guide rooted in the Health Stigma and Discrimination Framework (HSDF). We recruited participants online and through word of mouth via newsletters, blogs and social media. Participants were eligible to participate if they worked as a healthcare provider in Singapore or Canada during COVID-19. Following participant consent, data were recorded, transcribed verbatim, and coded using a framework approach. Coded data were charted into a framework matrix and used to compare themes in each country.

Results

We conducted 51 interviews (23 in Canada; 28 in Singapore). HCPs perceived that patient fears coupled with mistrust of the health system impacted health behaviors. HCPs reported discrimination and stigmatization of population subsets. In Singapore, this included Chinese tourists and migrant workers and in Canada, this included people of Chinese ethnicity and people experiencing homelessness. This stigma was often attributed to pre-existing prejudices including perceptions that these populations were at increased risk of COVID-19 or not adhering to public health recommendations. HCPs feared spreading COVID-19 to family, peers and patients, often resulting in participants choosing to isolate from social circles. HCPs in both countries experienced occupation-based stigma, including stigma related to public health practices (masking, testing); in Canada, this intersected with race-based prejudice for participants of Chinese ethnicity. HCPs in both samples witnessed and experienced stigmatizing behavior; some participants also experienced discrimination.

Conclusions

Secondary stigma related to occupation was experienced by HCPs during COVID-19. HCPs experienced intersecting stigma based on race/ethnicity and observed stigmatization of marginalized patient populations. Most themes were consistent across Canada and Singapore. Strategies to mitigate COVID-19 related stigma toward HCPs and at-risk patient populations are warranted.
Pre-pandemic cross-reactive antibody and cellular responses against SARS-CoV-2 among female sex workers in Dakar, Senegal
Authors: Herrera Bobby Brooke , Chaplin Beth , MBoup Souleymane , Abdullahi Adam , He Michelle , Fisher Sydney M. , Akanmu Sulaimon , Chang Charlotte A. , Hamel Donald J. , Gupta Ravindra K. , Kanki Phyllis J.
Published: January 2025

Background

The COVID-19 pandemic had a severe impact globally, yet African populations exhibited unexpectedly lower rates of severe disease and mortality. We investigated the potential role of pre-existing immunity in shaping the epidemiology of COVID-19 in Africa.

Methods

Plasma collected from Senegalese female sex workers prior to the COVID-19 pandemic was screened for SARS-CoV-2 and human coronavirus (hCoV) antibodies by virion immunoblots. For antibody-reactive plasma, paired peripheral blood mononuclear cells were stimulated by fusion proteins and IFN-γ cellular responses were assessed via ELISPOT.

Results

We observed substantial levels of pre-existing cross-reactive immunity to SARS-CoV-2, stemming from prior exposure to seasonal hCoVs. Our antibody analysis revealed a 23.5% (47/200) seroprevalence rate against SARS-CoV-2 nucleocapsid (N). These samples were then probed for antibodies against hCoV spike (S) and/or N antigens; 85.1% (40/47), 70.2% (33/47), and 95.7% (45/47) were antibody reactive against hCoV-229E, hCoV-OC43, or hCoV-HKU1, respectively. Our analysis of cellular responses also demonstrated cross-reactivity to SARS-CoV-2 with 80.0% (36/45) and 82.2% (37/45) showing IFN-γ responses against S and N, respectively. A unique pre-pandemic subject had cross-reactive SARS-CoV-2 S antibodies with detectable neutralization and cross-reactive cellular responses.

Conclusion

These findings suggest that prior hCoV exposure may induce cross-reactive adaptive immunity, potentially contributing to protection against COVID-19. Our study provides unique data on the dynamics of hCoV and SARS-CoV-2 immunity in Senegal and underscores the importance of understanding the role of pre-existing immunity in shaping COVID-19 outcomes globally.
Markers of immunosenescence in CMV seropositive healthy elderly adults
Authors: Rodríguez Ivón Johanna , Parra-López Carlos Alberto
Published: January 2025

A significant increase in life expectancy has accompanied the growth of the world’s population. Approximately 10% of the global population are adults over 60, and it is estimated that 2050 this figure will double. This increase in the proportion of older adults leads to a more significant burden of age-related diseases. Immunosenescence predisposes elderly individuals to a higher incidence of infectious and chronic non-communicable diseases with higher mortality rates. Despite advances in research, it is necessary to evaluate the cellular characteristics of the aging immune system in populations with a high incidence of latent viruses such as cytomegalovirus (CMV). In this sense, this work aimed to identify senescence markers in cells of the innate and adaptive immune system in healthy older adults with CMV infection. We observed that older adults present an increase in the population of CD14+CD16+ intermediate monocytes, an expansion of CD56neg NK cells with an increase in the expression of CD57, as well as a decrease in the naïve CD4+ and CD8+ T cells, accompanied by an increased expression of senescence markers CD57 and KLRG1 in effector CD8+ T cells.
Ten days of supplementation with a standardized Boswellia serrata extract attenuates soreness and accelerates recovery after repeated bouts of downhill running in recreationally active men
Authors: Salter Dawna , Yalamanchi Himana , Yalamanchi Aiswarya , Yalamanchi Amulya
Published: January 2025

Extracts derived from Indian frankincense (Boswellia serrata) effectively reduce the pain and swelling associated with osteoarthritis. It is unknown whether the anti-inflammatory and analgesic properties of B. serrata extend to muscle and joint pain resulting from high-impact eccentric exercise. This pilot study evaluated the efficacy of a standardized B. serrata extract LI51202F1 (SBS) to decrease soreness and improve recovery after repeated bouts of downhill running (DHR) compared to placebo (PLA). In total, 50 men (mean age 28 ± 4) were randomly allocated to consume 60 mg SBS or PLA once per day for 10 days (6 days before, the day of, and 3 days after DHR). On day 7, delayed soreness was induced by three 15-min DHR episodes on a 10% declined treadmill. Visual analog scale (VAS) scores of joint and muscle soreness, in addition to the maximal weight lifted for a one-repetition leg extension (1RM-LE) were assessed at baseline (pre-supplementation) and on days 8, 9, and 10. Blood and urine samples collected at baseline, before, and after DHR were analyzed for inflammation-related biomarkers. VAS scores significantly increased while muscle strength decreased from baseline measures after DHR regardless of group assignment (main effect of time p < 0.001). However, the subjects who received the supplement reported reduced muscle soreness on days 8, 9, and 10 compared to those who received the PLA. On day 9, peak soreness scores were lower in the SBS group than in the PLA group (p = 0.001). On day 10, the SBS group’s VAS scores were 8.0 ± 1.6 mm lower than the PLA group (p < 0.001). Supplementation improved recovery time as the 1RM-LE returned to baseline strength by day 10, with the subjects who received the supplement lifting 3.4 ± 1.2 kg more than the PLA group (p = 0.006). The SBS-supplemented subjects reported less knee joint pain after DHR than the PLA group (p < 0.05 on days 8, 9, and 10). C-reactive protein and interleukin-6 increased after DHR, but by day 10, SBS reduced these markers compared to the PLA (p < 0.05). This study suggests that SBS, a novel, standardized extract derived from the gum resin of B. serrata, improves recovery and reduces soreness following high-impact eccentric exercise.

Clinical Trial Registration

https://ctri.nic.in/Clinicaltrials/pubview2.php, Clinical Trial Registry of India (CTRI/2019/07/020323).
Fermented Bamboo Powder Affects Dwarf Yellow-Feathered Broiler Growth, Blood Biochemistry, Antioxidant Status, Intestinal Morphology, and Nutrient Transporter Gene Expression
Authors: Shoura Hytham Elsaid , Ding Wei , Hou Linsong , Malyar Rahmani Mohammad , Wei Quanwei , Zhou Weisheng , Shi Fangxiong
Published: January 2025

This study explores the effects of fermented bamboo powder (FBP) on the growth performance, antioxidant status, intestinal morphology, and expression of nutrient transporter genes in broiler chickens. Two groups were formed from 600 healthy 1-day-old chicks; each group included 30 chicks, repeated 10 times. The control group was fed a basal diet and supplemented the experimental group’s diet with 1.0 g/kg FBP during phase I (days 1–22) and 2.0 g/kg FBP during phase II (days 23–45). The findings revealed a significant enhancement in the growth performance for the group that received fermented bamboo powder in contrast to the control group (p < 0.05). The levels of triglycerides exhibited a significant reduction (p < 0.05), alongside a significant decrease in urea and creatinine levels (p < 0.05). The levels of malondialdehyde (MDA), a marker of oxidative stress, exhibited a significant reduction in the FBP group compared to the control group (p < 0.01). It was found that the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT) worked much better in the FBP group than in the control group (p < 0.01). On the other hand, fermented bamboo powder greatly increased the surface area that could absorb nutrients in the intestines (duodenum, jejunum, and ileum) by increasing the villus height, intestinal lumen depth, and villus area (p < 0.01). Compared to the control, FBP increased the expression levels of genes involved in the transport of nutrients from the intestinal regions (duodenum, jejunum, and ileum), including GLUT1, GLUT2, CAT1, CAT2, PEPT1, PEPT2, and LAT1. The upregulation of nutrient transporter genes further facilitated nutrient absorption, contributing to the observed improvements in growth and body weight. These findings endorse FBP as a viable feed additive in broiler diets to enhance health and performance.
Interpretable LAI Fine Inversion of Maize by Fusing Satellite, UAV Multispectral, and Thermal Infrared Images
Authors: Yao Yu , Wang Hengbin , Yang Xiao , Gao Xiang , Yang Shuai , Zhao Yuanyuan , Li Shaoming , Zhang Xiaodong , Liu Zhe
Published: January 2025

Leaf area index (LAI) serves as a crucial indicator for characterizing the growth and development process of maize. However, the LAI inversion of maize based on unmanned aerial vehicles (UAVs) is highly susceptible to various factors such as weather conditions, light intensity, and sensor performance. In contrast to satellites, the spectral stability of UAV-based data is relatively inferior, and the phenomenon of “spectral fragmentation” is prone to occur during large-scale monitoring. This study was designed to solve the problem that maize LAI inversion based on UAVs is difficult to achieve both high spatial resolution and spectral consistency. A two-stage remote sensing data fusion method integrating coarse and fine fusion was proposed. The SHapley Additive exPlanations (SHAP) model was introduced to investigate the contributions of 20 features in 7 categories to LAI inversion of maize, and canopy temperature extracted from thermal infrared images was one of them. Additionally, the most suitable feature sampling window was determined through multi-scale sampling experiments. The grid search method was used to optimize the hyperparameters of models such as Gradient Boosting, XGBoost, and Random Forest, and their accuracy was compared. The results showed that, by utilizing a 3 × 3 feature sampling window and 9 features with the highest contributions, the LAI inversion accuracy of the whole growth stage based on Random Forest could reach R2 = 0.90 and RMSE = 0.38 m2/m2. Compared with the single UAV data source mode, the inversion accuracy was enhanced by nearly 25%. The R2 in the jointing, tasseling, and filling stages were 0.87, 0.86, and 0.62, respectively. Moreover, this study verified the significant role of thermal infrared data in LAI inversion, providing a new method for fine LAI inversion of maize.
Advanced Deep Learning Methods for Multiple Behavior Classification of Cage-Free Laying Hens
Authors: Subedi Sachin , Bist Ramesh Bahadur , Yang Xiao , Li Guoming , Chai Lilong
Published: January 2025

The welfare of hens in cage-free systems is closely linked to their behaviors, such as feeding, drinking, pecking, perching, bathing, preening, and foraging. To monitor these behaviors, we developed and evaluated deep learning models based on YOLO (You Only Look Once), an advanced object detection technology known for its high accuracy, speed, and compact size. Three YOLO-based models—YOLOv5s_BH, YOLOv5x_BH, and YOLOv7_BH—were created to track and classify the behaviors of laying hens in cage-free environments. A dataset comprising 1500 training images, 500 validation images, and 50 test images was used to train and validate the models. The models successfully detected poultry behaviors in test images with bounding boxes and objectness scores ranging from 0 to 1. Among the models, YOLOv5s_BH demonstrated superior performance, achieving a precision of 78.1%, surpassing YOLOv5x_BH and YOLOv7_BH by 1.9% and 2.2%, respectively. It also achieved a recall of 71.7%, outperforming YOLOv5x_BH and YOLOv7_BH by 1.9% and 2.8%, respectively. Additionally, YOLOv5s_BH recorded a mean average precision (mAP) of 74.6%, exceeding YOLOv5x_BH by 2.6% and YOLOv7_BH by 9%. While all models demonstrated high detection precision, their performance was influenced by factors such as stocking density, varying light conditions, and obstructions from equipment like drinking lines, perches, and feeders. This study highlights the potential for the automated monitoring of poultry behaviors in cage-free systems, offering valuable insights for producers.
Effects of Mung Bean Residue Return and Biochar Amendment Combined with Reduction in Inorganic Fertilizer on Rice Yield and Nutrient Uptake: A Case Study in Mekong Delta, Vietnam
Authors: Linh Doan Thi Truc , Khoi Chau Minh , Dung Tran Van , Khanh Tran Huynh , Sinh Nguyen Van , Phuong Nguyen Thi Kim , My Huynh Mach Tra , Toyota Koki
Published: January 2025

This study aimed to assess the co-incorporation of mung bean residue and rice husk biochar with reduced NPK fertilizer rates on rice yield and nutrient uptake in the subsequent rice crop. A field experiment was conducted in five treatments (T1 to T5). In the spring–summer (SS) of 2023, rice was cultivated and its straw was burned (T1), while mung bean was cultivated and its residue was incorporated (T2 to T5). In the next summer–autumn crop (SA), rice was cultivated with different levels of inorganic fertilizers. T1 was added with the conventional fertilizer (95 kg N, 45 kg P2O5, and 35 kg K2O ha−1). T2 included the same amount of NPK fertilizer as T1 with mung bean incorporation. In T3 to T5, rice husk biochar was amended at a rate of 10 Mg ha−1 before SA. In T3, inorganic fertilizers were reduced by 30% of N and 50% of P2O5 and K2O; in T4, by 15% of N, 30% of P2O5 and K2O; and in T5, by 15% of N only. The rice grain yield was 26.6–35.3% significantly higher in T3, T4, and T5 compared to T1. P accumulation in straw and grain was significantly higher in T3, T4, and T5 than in T1. Furthermore, K accumulation in grain was markedly higher in T3, T4, and T5. No significant differences were observed in any of the soil chemical properties among treatments at harvest in SA. This study highlights that the combination of residue incorporation and biochar may substitute a part of chemical fertilizers and contribute to more sustainable rice production.
Non-Destructive Detection of pH Value During Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging Technology
Authors: Xue Xiaoyu , Tian Haiqing , Zhao Kai , Yu Yang , Zhuo Chunxiang , Xiao Ziqing , Wan Daqian
Published: January 2025

The pH value of maize silage can accurately reflect its quality. In this study, a colorimetric sensor array (CSA) combined with hyperspectral imaging (HSI) was used to predict the pH value of maize silage during secondary fermentation. Seventeen color-sensitive dyes were used to construct the CSA, which was subsequently applied to capture the volatile odor profiles of maize silage samples. Hyperspectral images of the color-sensitive dyes on the CSA were acquired using the HSI technique. Different algorithms were used to preprocess the raw spectral data of each dye, and a partial least squares regression (PLSR) model was built for each dye separately. Subsequently, the adaptive bacterial foraging optimization (ABFO) algorithm was employed to identify three color-sensitive dyes that demonstrated heightened sensitivity to pH variations in maize silage. This study further compared the capabilities of individual dyes, as well as their combinations, in predicting the pH value of maize silage. Additionally, a novel feature wavelength extraction method based on the ABFO algorithm was proposed, which was then compared with two traditional feature extraction algorithms. These methods were combined with PLSR and backpropagation neural network (BPNN) algorithms to construct a quantitative prediction model for the pH value of maize silage. The results show that the quantitative prediction model constructed based on three dyes was more accurate than that constructed based on an individual dye. Among them, the ABFO-BPNN model constructed on the basis of combined dyes had the best prediction performance, with prediction correlation coefficient (RP2), root mean square error of the prediction set (RMSEP), and ratio of performance deviation (RPD) values of 0.9348, 0.3976, and 3.9695, respectively. The aim of this study was to develop a reliable evaluation model to achieve fast and accurate predictions of silage pH.
Impact of Autolysed Brewer’s Yeast and Soluble Dried Yeast Extract on Growth Performance and Mucosal Health of Atlantic Salmon (Salmo salar) Parr
Authors: Odu-Onikosi Sheu G. , Momoh Taofik A. , Abarra Sherilyn T. , Wood Noah E. , Amulejoye Folasade D. , Emery Matthew , Harper Glenn M. , Eynon Benjamin , Kuri Victor , Kühlwein Holger , Merrifield Daniel L.
Published: January 2025

Yeast-based feed additives have emerged as promising functional feed additives (FFAs) to promote sustainable aquaculture development through enhanced gut health and immune modulation in fish. The present study evaluated the impact of autolysed brewer’s yeast (ABY) and soluble dried yeast extract (SDYE) in improving the intestinal and skin histology, immune response, and intestinal microbiome of Atlantic salmon parr (Salmo salar) over a 9-week feeding trial. Three experimental diets were produced: a control diet, a diet supplemented with ABY at 2.5 g/kg, and a diet supplemented with SDYE at 2.5 g/kg. These diets were administered to triplicate tanks of Atlantic salmon. The yeast-supplemented diets, especially ABY, improved intestinal mucosal fold length, lamina propria width, microvilli density, and intestinal goblet cell counts, as well as skin goblet cell counts. The yeast additives had no detrimental effects on the fish haematology, with no significant differences in haemoglobin concentration, red blood cell counts, and white blood cell counts among the treatment groups. Gene expression analysis revealed upregulation of il-1β and muc-2 in fish fed the ABY diet, indicating enhanced immune function and potentially mucosal protection. Intestinal microbiota analysis revealed Firmicutes as the most dominant phylum in all groups, followed by Actinobacteriota. Distinct bacterial community shifts were observed between the treatment groups, with a significant increase in the relative abundance of taxa such as Staphylococcus in yeast-supplemented diets and a significant decrease in Streptococcus and Weissella. Collectively, these findings suggest that the yeast additives, especially ABY, enhance gut health and immune function without compromising growth performance.
FTGM: Fast Transformer-Based Global Matching for Particle Image Velocimetry
Authors: Ding Shuaimin , Zhao Tianqing , Yang Jun , Zhang Dezhi
Published: January 2025

The integration of deep learning with optical flow estimation in Particle Image Velocimetry (PIV) represents an emerging solution. Extensive research indicates that deep learning has potential to match or outperform state-of-the-art classical algorithms in efficiency, accuracy, and spatial resolution. However, current learning-based methods, which rely on cost volumes and convolutions for flow regression, are limited to local correlations. This limitation hinders the capture of global information. While extensive iterative refinements enhance the quality of prediction flows, they also result in a linear increase in inference time. To enhance both efficiency and accuracy, we propose a global matching method for PIV. This method directly compares feature similarities to identify correspondences between images and generate estimated flows. The underlying idea is to first extract initial features of particle image pairs, then enhance these features through a Transformer specifically designed for PIV, and perform operations for feature correlation matching, followed by global optical flow propagation and optimization. Additionally, higher-resolution features are introduced for refinement. By employing both synthetic and experimental data, including benchmark sets and data from turbulent wave channel flow experiments, we demonstrate that global matching method in PIV achieves superior efficiency and accuracy compared to existing learning-based methods.
Enhancing Conversational Agent Development Through a Semi-Automatization Development Proposal
Authors: Martínez-Gárate Ángel , Aguilar-Calderón José Alfonso , Tripp-Barba Carolina , Zaldívar-Colado Aníbal
Published: January 2025

The development of chatbots is often hindered by high costs and time consumption, with existing technologies and frameworks not fully addressing the diverse requirements for creating robust conversational agents across platforms like WhatsApp. This is a limitation for the implementation of these frameworks in a professional environment, thus representing both opportunities and complexities. This article presents improvements to the Xatkit framework, utilizing Model-Driven Development techniques to simplify chatbot development and extend support for WhatsApp. Additionally, the integration of the GPT-3 autoregressive language model enhances user interaction, offering a more sophisticated and responsive conversational experience.
Free Vibrations and Flutter Analysis of Composite Plates Reinforced with Carbon Nanotubes
Authors: Chwał Małgorzata
Published: January 2025

This paper considers the free vibration and flutter of carbon nanotube (CNT) reinforced nanocomposite plates subjected to supersonic flow. From the literature review, a great deal of research has been conducted on the free vibration and flutter response of high-volume CNT/nanocomposite structures; however, there is little research on the flutter instability of low-volume CNT/nanocomposite structures. In this study, free vibration and flutter analysis of classical CNT/nanocomposite thin plates with aligned and uniformly distributed reinforcement and low CNT volume fraction are performed. The geometry of the CNTs and the definition of the nanocomposite material properties are considered. The nanocomposite properties are estimated based on micromechanical modeling, while the governing relations of the nanocomposite plates are derived according to Kirchhoff’s plate theory with von Karman nonlinear strains. Identification of vibrational modes for nanocomposite thin plates and analytical/graphical evaluation of flutter are presented. The novel contribution of this work is the analysis of the eigenfrequencies and dynamic instabilities of nanocomposite plates with a low fraction of CNTs aligned and uniformly distributed in the polymer matrix. This article is helpful for a comprehensive understanding of the influence of a low-volume fraction and uniform distribution of CNTs and boundary conditions on the dynamic instabilities of nanocomposite plates.
Multimodal Natural Disaster Scene Recognition with Integrated Large Model and Mamba
Authors: Shao Yuxuan , Xu Liwen
Published: January 2025

The accurate identification of natural disasters is crucial in ensuring effective post-disaster relief efforts. However, the existing models for disaster classification often incur high costs. To address this, we propose leveraging the most advanced pre-trained large language models, which offer superior generative and multimodal understanding capabilities. Using a question-answering approach, we extract textual descriptions and category prediction probabilities for disaster scenarios, which are then used as input to our proposed Mamba Multimodal Disaster Recognition Network (Mamba-MDRNet). This model integrates a large pre-trained model with the Mamba mechanism, enabling the selection of the most reliable modality information as a robust basis for scene classification. Extensive experiments demonstrate consistent performance improvements across various visual models with heterogeneous architectures. Notably, integrating EfficientNet within Mamba-MDRNet yielded 97.82% accuracy for natural scene classification, surpassing the performance of the CNN (91.75%), ViT (94.50%), and ResNet18 (97.25%). These results highlight the potential of multimodal models combining large models and the Mamba mechanism for disaster type prediction.
Analysis of Tunnel Lining Damage Characteristics Under the Combined Actions of Fault Dislocation and Seismic Action
Authors: Du Jiaxuan , Yan Songhong , Sun Weiyu , Li Yuxiang , Cao Mingxing
Published: January 2025

Tunnels crossing active faults frequently experience simultaneous exposure to fault dislocation and seismic action during operation. To study the damage behavior of tunnels under the combined effects of fault dislocation and seismic action, a three-dimensional nonlinear finite element model was established. This model simulates fault dislocation superimposed on seismic action in the context of tunnel engineering through active faults. The main conclusions are as follows: (1) The acceleration amplification phenomenon occurs in the tunnels after the superposition of seismic action; at the same time, the degree and scope of tunnel damage increase significantly, in which the increase in tensile damage is more significant. (2) The initial damage from fault dislocation worsens tunnel damage under seismic action, as evidenced by the energy dissipation characteristics. (3) As the initial fault displacement and peak seismic acceleration increase, the extent of lining damage also increases. Notably, compressive damage to the lining is symmetrically distributed along the fault plane, whereas tensile damage is significantly more severe within the fault rupture zone. (4) Even moderate earthquakes can cause severe damage to tunnels crossing active faults. Therefore, tunnel construction in these areas must include disaster prevention and mitigation strategies.
Development of Navigation Network Models for Indoor Path Planning Using 3D Semantic Point Clouds
Authors: Hou Jiwei , Hübner Patrick , Iwaszczuk Dorota
Published: January 2025

Accurate and efficient path planning in indoor environments relies on high-quality navigation networks that faithfully represent the spatial and semantic structure of the environment. Three-dimensional semantic point clouds provide valuable spatial and semantic information for navigation tasks. However, extracting detailed navigation networks from 3D semantic point clouds remains a challenge, especially in complex indoor spaces like staircases and multi-floor environments. This study presents a comprehensive framework for developing and extracting robust navigation network models, specifically designed for indoor path planning applications. The main contributions include (1) a preprocessing pipeline that ensures high accuracy and consistency of the input semantic point cloud data; (2) a moving window algorithm for refined node extraction in staircases to enable seamless navigation across vertical spaces; and (3) a lightweight, JSON-based storage structure for efficient network representation and integration. Additionally, we presented a more comprehensive sub-node extraction method for hallways to enhance network continuity. We validated the method using two datasets—the public S3DIS dataset and the self-collected HoloLens 2 dataset—and demonstrated its effectiveness through Dijkstra-based path planning. The generated navigation networks supported practical scenarios such as wheelchair-accessible path planning and seamless multi-floor navigation. These findings highlight the practical value of our approach for modern indoor navigation systems, with potential applications in smart building management, robotics, and emergency response.
P-Algebras
Authors: Edeghagba Elijah Eghosa , Šešelja Branimir , Tepavčević Andreja
Published: January 2025

Following the notions of Ω-set and Ω-algebra where Ω is a complete lattice, we introduce P-algebras, replacing the lattice Ω by a poset P. A P-algebra is a classical algebraic structure in which the usual equality is replaced by a P-valued equivalence relation, i.e., with the symmetric and transitive map from the underlying set into a poset P. In addition, this generalized equality is (as a map) compatible with the fundamental operations of the algebra. The diagonal restriction of this map is a P-valued support of a P-algebra. The particular subsets of this support, its cuts, are classical subalgebras, while the cuts of the P-valued equality are congruences on the corresponding cut subalgebras. We prove that the collection of the corresponding quotients of these cuts is a centralized system in the lattice of weak congruences of the basic algebra. We also describe the canonical representation of P-algebras, independent of the poset P.
Probability, Statistics and Estimation
Authors: Gómez Yolanda M. , Barranco-Chamorro Inmaculada
Published: January 2025

This Special Issue of Axioms, entitled “Probability, Statistics and Estimation”, comprises 15 papers that were accepted for publication after a rigorous review process [...]