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Hi-C and Micro-C are the three-dimensional (3D) genome assays that use high-throughput sequencing. In the analysis, the sequenced paired-end reads are mapped to a reference genome to generate a two-dimensional contact matrix for identifying topologically associating domains (TADs), chromatin loops, and chromosomal compartments. On the other hand, the distance distribution of the paired-end mapped reads also provides insight into the 3D genome structure by highlighting global contact frequency patterns at distances indicative of loops, TADs, and compartments. This chapter presents a basic workflow for visualizing and analyzing contact distance distributions from Hi-C data. The workflow can be run on Google Colaboratory, which provides a ready-to-use Python environment accessible through a web browser. The notebook that demonstrates the workflow is available in the GitHub repository at https://github.com/rnakato/Springer_contact_distance_plot.

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La evaluación de la marcha en cinta caminadora puede resultar relevante para la toma de decisiones clínicas. No obstante, factores demográficos como la edad y el IMC pueden alterar la interpretación de los resultados. Nuestro objetivo fue obtener variables espacio- temporales, energéticas y costo de transporte durante la velocidad autoseleccionada en cinta caminadora para una muestra representativa de adultos uruguayos (n=28) y evaluar si diferentes rangos de edades e IMC pueden ser factores a tener en cuenta en pruebas clínicas donde se consideren dichas variables. Participaron 17 hombres y 11 mujeres (39,3 ± 14,8 años, 75,9 ± 12,5 kg, 1,74 ± 0,09 m, IMC 25,2 ± 4,06). Se realizó una reconstrucción 3D del movimiento en forma sincronizada con el consumo energético. Se obtuvieron valores de referencia y luego de agrupar los participantes según su IMC y rango de edad se compararon los datos mediante test de t (p≤0.05). Los resultados revelaron discrepancias significativas en las medidas espacio-temporales y energéticas de los adultos uruguayos al caminar en cinta con respecto a la literatura. La marcha difiere entre adultos jóvenes y de mediana edad en su velocidad autoseleccionada (p=0,03), longitud de zancada (p=0,01), trabajo mecánico externo (<0,001) y recuperación de energía mecánica (0,009), destacando la importancia de considerar la edad en evaluaciones clínicas. El IMC no influyó significativamente en estas variables. Estos hallazgos subrayan la necesidad de ajustar las interpretaciones de las pruebas clínicas de la marcha sobre cinta caminadora en adultos uruguayos de mediana edad (45 a 65 años).

Treadmill gait assessment can be relevant for clinical decision-making. However, demographic factors such as age and BMI may alter result interpretation. Our aim was to obtain spatiotemporal, energetic, and cost of transport variables during self-selected treadmill walking speed for a representative sample of Uruguayan adults (n=28) and to assess if different age ranges and BMI could be factors to consider in clinical tests involving these variables. Seventeen men and eleven women participated (39.3 ± 14.8 years, 75.9 ± 12.5 kg, 1.74 ± 0.09 m, BMI 25.2 ± 4.06). A synchronized 3D motion reconstruction was performed with energy consumption. Reference values were obtained and data were compared using t-tests (p≤0.05), after grouping participants by BMI and age range. Results revealed significant discrepancies in spatiotemporal and energetic measures of Uruguayan adults walking on the treadmill, compared to the literature. Gait differed between young and middle-aged adults in their self-selected speed (p=0.03), stride length (p=0.01), external mechanical work (p<0.001), and mechanical energy recovery (0.009), emphasizing the importance of considering age in clinical evaluations. BMI did not significantly influence these variables. These findings underscore the need to adjust interpretations of treadmill gait clinical tests in middle-aged Uruguayan adults (45 to 65 years).

A avaliação da marcha na esteira pode ser relevante para a tomada de decisões clínicas. No entanto, fatores demográficos como idade e IMC podem alterar a interpretação dos resultados. Nosso objetivo foi obter variáveis espaço-temporais, energéticas e custo de transporte durante a velocidade de caminhada autoselecionada na esteira para uma amostra representativa de adultos uruguaios (n = 28) e avaliar se diferentes faixas etárias e IMC podem ser fatores a serem considerados em testes clínicos que envolvam essas variáveis. Dezessete homens e onze mulheres participaram (39,3 ± 14,8 anos, 75,9 ± 12,5 kg, 1,74 ± 0,09 m, IMC 25,2 ± 4,06). Foi realizada uma reconstrução tridimensional do movimento sincronizada com o consumo de energia. Foram obtidos valores de referência e os dados foram comparados usando testes t (p≤0,05), após agrupar os participantes por IMC e faixa etária. Os resultados revelaram discrepâncias significativas nas medidas espaço-temporais e energéticas dos adultos uruguaios ao caminhar na esteira, em comparação com a literatura. A marcha diferiu entre adultos jovens e de meia-idade em sua velocidade autoselecionada (p=0,03), comprimento da passada (p=0,01), trabalho mecânico externo (<0,001) e recuperação de energia mecânica (0,009), destacando a importância de considerar a idade em avaliações clínicas. O IMC não influenciou significativamente essas variáveis. Esses achados destacam a necessidade de ajustar as interpretações dos testes clínicos de marcha na esteira em adultos uruguaios de meia- idade (45 a 65 anos).

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The existence of viable human pathogens in bioaerosols which can cause infection or affect human health has been the subject of little research. In this study, data provided by 10 tropospheric aircraft surveys over Japan in 2014 confirm the existence of a vast diversity of microbial species up to 3,000 m height, which can be dispersed above the planetary boundary layer over distances of up to 2,000 km, thanks to strong winds from an area covered with massive cereal croplands in Northeast (NE) Asia. Microbes attached to aerosols reveal the presence of diverse bacterial and fungal taxa, including potential human pathogens, originating from sewage, pesticides, or fertilizers. Over 266 different fungal and 305 bacterial genera appeared in the 10 aircraft transects. Actinobacteria, Bacillota, Proteobacteria, and Bacteroidetes phyla dominated the bacteria composition and, for fungi, Ascomycota prevailed over Basidiomycota. Among the pathogenic species identified, human pathogens include bacteria such as Escherichia coli, Serratia marcescens, Prevotella melaninogenica, Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus saprophyticus, Cutibacterium acnes, Clostridium difficile, Clostridium botulinum, Stenotrophomonas maltophilia, Shigella sonnei, Haemophillus parainfluenzae and Acinetobacter baumannii and health-relevant fungi such as Malassezia restricta, Malassezia globosa, Candida parapsilosis and Candida zeylanoides, Sarocladium kiliense, Cladosporium halotolerans, and Cladosporium herbarum. Diversity estimates were similar at heights and surface when entrainment of air from high altitudes occurred. Natural antimicrobial-resistant bacteria (ARB) cultured from air samples were found indicating long-distance spread of ARB and microbial viability. This would represent a novel way to disperse both viable human pathogens and resistance genes among distant geographical regions.

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The genetic code plays a central role in all living organisms and its modeling is important for describing and understanding involved the coding rules. There are many approaches to modeling various aspects of the genetic code. One of the simple and successful mathematical tools for modeling the similarity both between codons and between amino acids, is the ultrametrics and especially the p-adic distance. This article contains an overview of ultrametric (p-adic) modeling of genetic information, and its translation to proteins using the genetic code.

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An unavoidable consequence of chicken meat production is the generation of substantial quantities of spent litter. This poses several environmental and social challenges, as broiler farms become hotspots for odour emissions. The main source of odour from broiler litter is the microbial decomposition of organic material. Thus, lignite's previously shown capacity to reduce microbial activity in broiler litter was expected to reduce odour emissions from broiler housing. The effect of lignite on odour emission rate (OER) (ou/s) was investigated using dynamic olfactometry over two consecutive summer broiler grow-out cycles in Victoria, Australia, with lignite applied at 3.5 kg/m2. The air quality dispersion model, AERMOD, was used to investigate how lignite's effect on OER influenced the predicted odour dispersion distances and concentrations in the context of various Australian regulatory requirements. Additionally, the effect of lignite on bird production performance was also determined. This study showed that lignite reduced the OER from commercial broiler housing by an average of 56% over both grow-outs. This effect was observed for the duration of the trial. The observed reduction in OER reduced the required separation distances by 44-53% according to the state odour criteria for Victoria, New South Wales, Queensland and South Australia. There were no observed differences in feed conversion ratio, bird live weight or mortality throughout either grow-out. This study demonstrated the capacity of lignite to reduce odour emissions from commercial broiler housing without reducing bird production performance.

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BACKGROUND: Pulmonary hypertension (PH) is a life-threatening condition with high mortality, categorized into 5 Groups based on distinct etiologies. Fasudil, a potent vasodilator targeting the RhoA/Rho kinase pathway, holds promise for diverse PH pathologies. However, a comprehensive systematic evaluation of its clinical benefits remains elusive. METHODS: We conducted a systematic search across several databases. Meta-analysis using odds ratio and mean difference was performed, with an assessment of studies' quality and pooled evidence. RESULTS: Studies on Group-2 and -3 PH reports eligible data for meta-analysis. Inclusion of 3269 patients with Group-3 PH demonstrated that fasudil significantly increased effective events, FEV1, 6-minute walking distance (6MWD) and arterial PaO2, and decreased mean pulmonary artery pressure (mPAP) and pulmonary artery systolic pressure (PASP); Inclusion of 197 patients with Group-2 PH suggested that fasudil significantly increased 6MWD and PaO2, and decreased PASP. Subgroup analysis revealed no significant difference between dosages of 30 and 60 mg/day, while durations and methods of fasudil administration might affect therapeutic effectiveness in patients with Group-3 PH. CONCLUSIONS: By providing comprehensive and robust evidence, our study favor the beneficial effects of fasudil by enhancing FEV1, 6MWD and PaO2, and reducing mPAP and PASP on patients with Group-3 PH, suggesting fasudil as a viable treatment recommendation for these patients and highlighting the need for further studies to inform healthcare policies. PROTOCOL REGISTRATION: www.crd.york.ac.uk/prospero identifier is CRD42022308947.

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Precise measurement of fiber diameter in animal and synthetic textiles is crucial for quality assessment and pricing; however, traditional methods often struggle with accuracy, particularly when fibers are densely packed or overlapping. Current computer vision techniques, while useful, have limitations in addressing these challenges. This paper introduces a novel deep-learning-based method to automatically generate distance maps of fiber micrographs, enabling more accurate fiber segmentation and diameter calculation. Our approach utilizes a modified U-Net architecture, trained on both real and simulated micrographs, to regress distance maps. This allows for the effective separation of individual fibers, even in complex scenarios. The model achieves a mean absolute error (MAE) of 0.1094 and a mean square error (MSE) of 0.0711, demonstrating its effectiveness in accurately measuring fiber diameters. This research highlights the potential of deep learning to revolutionize fiber analysis in the textile industry, offering a more precise and automated solution for quality control and pricing.

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Detection of abnormal situations in mobile systems not only provides predictions about risky situations but also has the potential to increase energy efficiency. In this study, two real-world drives of a battery electric vehicle and unsupervised hybrid anomaly detection approaches were developed. The anomaly detection performances of hybrid models created with the combination of Long Short-Term Memory (LSTM)-Autoencoder, the Local Outlier Factor (LOF), and the Mahalanobis distance were evaluated with the silhouette score, Davies-Bouldin index, and Calinski-Harabasz index, and the potential energy recovery rates were also determined. Two driving datasets were evaluated in terms of chaotic aspects using the Lyapunov exponent, Kolmogorov-Sinai entropy, and fractal dimension metrics. The developed hybrid models are superior to the sub-methods in anomaly detection. Hybrid Model-2 had 2.92% more successful results in anomaly detection compared to Hybrid Model-1. In terms of potential energy saving, Hybrid Model-1 provided 31.26% superiority, while Hybrid Model-2 provided 31.48%. It was also observed that there is a close relationship between anomaly and chaoticity. In the literature where cyber security and visual sources dominate in anomaly detection, a strategy was developed that provides energy efficiency-based anomaly detection and chaotic analysis from data obtained without additional sensor data.

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Within the context of smart transportation and new infrastructure, Vehicle-to-Everything (V2X) communication has entered a new stage, introducing the concept of holographic intersection. This concept requires roadside sensors to achieve collaborative perception, collaborative decision-making, and control. To meet the high-level requirements of V2X, it is essential to obtain precise, rapid, and accurate roadside information data. This study proposes an automated vehicle distance detection and warning scheme based on camera video streams. It utilizes edge computing units for intelligent processing and employs neural network models for object recognition. Distance estimation is performed based on the principle of similar triangles, providing safety recommendations. Experimental validation shows that this scheme can achieve centimeter-level distance detection accuracy, enhancing traffic safety. This approach has the potential to become a crucial tool in the field of traffic safety, providing intersection traffic target information for intelligent connected vehicles (ICVs) and autonomous vehicles, thereby enabling V2X driving at holographic intersections.

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The deep integration of communication and sensing technology in fiber-optic systems has been highly sought after in recent years, with the aim of rapid and cost-effective large-scale upgrading of existing communication cables in order to monitor ocean activities. As a proof-of-concept demonstration, a high-degree of compatibility was shown between forward-transmission distributed fiber-optic vibration sensing and an on-off keying (OOK)-based communication system. This type of deep integration allows distributed sensing to utilize the optical fiber communication cable, wavelength channel, optical signal and demodulation receiver. The addition of distributed sensing functionality does not have an impact on the communication performance, as sensing involves no hardware changes and does not occupy any bandwidth; instead, it non-intrusively analyzes inherent vibration-induced noise in the data transmitted. Likewise, the transmission of communication data does not affect the sensing performance. For data transmission, 150 Mb/s was demonstrated with a BER of 2.8 × 10-7 and a QdB of 14.1. For vibration sensing, the forward-transmission method offers distance, time, frequency, intensity and phase-resolved monitoring. The limit of detection (LoD) is 8.3 pε/Hz1/2 at 1 kHz. The single-span sensing distance is 101.3 km (no optical amplification), with a spatial resolution of 0.08 m, and positioning accuracy can be as low as 10.1 m. No data averaging was performed during signal processing. The vibration frequency range tested is 10-1000 Hz.

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Objective: We aimed to evaluate medical school students' knowledge and approaches regarding telehealth. Method: In this descriptive study, an electronic survey was conducted among students attending the Faculties of Medicine at Health Sciences University. The first part of the Form included questions evaluating individual characteristics and telehealth approaches, and the second part included opinions and suggestions regarding telehealth usage topics. Results: Of 698 participants, 435 (64.9%) students were in the preclinical period. One hundred nine (15.6%) believed they had sufficient knowledge about telehealth while 399 (57.2%) believed that telehealth should be included in medical education. When asked about their opinions on using telehealth in their professional careers, 298 (42.7%) stated that they considered using them. Those who perceived themselves as having sufficient knowledge about telehealth were more inclined to consider using it more in their professional careers (p=0.000). Participants who believed that healthcare services could be provided through telehealth were more likely to think that disease monitoring would be better, patient follow-up quality would improve, unnecessary hospital admissions would decrease (p<0.05). Conclusions: The majority of medical faculty students lack sufficient knowledge about telemedicine and believe that education on this topic should be included in the medical curriculum. It is suggested that incorporating pre-clinical courses on telemedicine and providing internship opportunities in practical settings would effectively address this gap.

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BACKGROUND: Although the percentage of the population with a high degree of obesity (body mass index [BMI] ≥ 35 kg/m2) is low in Japan, the prevalence of obesity-related diseases in patients with high-degree obesity is greater than that in patients with a BMI < 35 kg/m2. Therefore, treatment for high-degree obesity is important. However, clinical studies have reported that 20-50% of patients with obesity discontinue weight-loss treatment in other countries. The circumstances surrounding antiobesity agents are quite different between Japan and other countries. In this study, we investigated the predictors of treatment discontinuation in Japanese patients with high-degree obesity. METHODS: We retrospectively reviewed the medical charts of 271 Japanese patients with high-degree obesity who presented at Toho University Sakura Medical Center for obesity treatment between April 1, 2014, and December 31, 2017. The patients were divided into non-dropout and dropout groups. Patients who discontinued weight-loss treatment within 24 months of the first visit were defined as "dropouts." Multivariate Cox proportional hazards regression analysis and Kaplan-Meier survival analysis were performed to examine the factors predicting treatment withdrawal. RESULTS: Among the 271 patients, 119 (43.9%) discontinued treatment within 24 months of the first visit. The decrease in BMI did not significantly differ between the two groups. No prescription of medication and residential distance from the hospital exceeding 15 km were the top contributors to treatment discontinuation, and the absence of prescription medication was the most important factor. The dropout-free rate was significantly higher in patients with medication prescriptions than in those without and in patients who lived within 15 km of the hospital than in those who lived farther than 15 km from the hospital. CONCLUSIONS: No medication prescription and longer residential distance from the hospital were associated with treatment dropout in Japanese patients with high-degree obesity; therefore, the addition of antiobesity medications and telemedicine may be necessary to prevent treatment discontinuation in such patients.

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OBJECTIVE: To compare unproctored and proctored online exams among chiropractic students. METHODS: Pre-existing data of 234 students across 4 consecutive endocrinology classes were analyzed for this study. The course was comprised of 3 lectures (50 minutes per lecture) each week. Student performance was evaluated by midterm exam and summative exam (S1). The students from 3 classes were asked to take a voluntary second summative exam (S2) approximately 7 months after the S1. Since this study was partially conducted during the COVID pandemic, some classes took the midterm and the S1 proctored in the classroom while others took them unproctored from a remote location. RESULTS: The mean midterm exam (p < .001) and S1 scores (p = .01) for the unproctored group (93.6 ± 7.0 and 88.8 ± 8.2) were significantly higher than the proctored group (88.1 ± 8.2 and 83.9 ± 11.2). The mean time taken by students was much greater for the unproctored exams than for the proctored exams (midterm: 40.7 ± 10.2 versus 16.7 ± 7.0, p < .001; S1: 47.0 ± 8.7 versus 21.5 ± 9.0, p < .001). By contrast, the mean unproctored S2 scores were lower than the proctored group (60.2 ± 14.7 versus 88.1 ± 8.2, p < .001). A linear regression test showed that the final exam was a statistically significant predictor of the recall exam (p < .01, R2 = 28.3%). CONCLUSION: The findings suggest that student performance is significantly altered by test format.

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DNA nanotechnology plays a crucial role in precise cancer medicine. Currently, molecular logic circuits are applied to detect tumor-specific biomarkers and control the release of therapeutic drugs. However, these systems lack self-learning capabilities for intelligent diagnostics in biological samples, and their data processing capabilities are limited. Here, a molecular learning vector quantization neural network (LVQNN) model based on DNA strand displacement (DSD) technology for breast tumor diagnosis is developed. Compared to previous work, the molecular LVQNN boasts powerful computing abilities, handling high-dimensional data for intelligent cancer diagnosis. To verify the feasibility and versatility of the network, two distinct typical datasets are selected: one from a single source with cell morphology data from 569 cases, and a more extensive one spanning different populations and ages, with miRNA gene expression data from 1881 cases. By using the molecular LVQNN, diagnostic experiments are conducted on 50 and 120 public individuals from these two datasets, respectively, achieving accuracy rates of 94% and 97.5%. This study demonstrates that the LVQNN model exhibits significant advantages in breast cancer diagnosis and enhances diagnostic accuracy while introducing new approaches for intelligent cancer diagnosis, anticipated to bring significant breakthroughs and application prospects to precise cancer medicine.

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PURPOSE: The purpose of this study is to report the parameter characteristics of the femoral anteversion angle (FAA) and tibial tubercle-trochlear groove (TT-TG) distance in patients with patellar instability compared to healthy individuals and to evaluate their reliability in predicting patellar dislocation, providing potential indications for osteotomy. METHODS: A retrospective collection of consecutive patients with patellar instability constituted the study group, while individuals without patellofemoral disorder served as the control group. Measurement of the FAA and TT-TG distance were conducted by lower extremity computed tomography scans and knees with true patellar dislocation were recorded. The diagnostic capability of the FAA and TT-TG distance was assessed using receiver operating characteristic curves and area under the curve (AUC), determining the pathological values by sensitivity and specificity. RESULTS: The FAA (21.6 ± 9.0°) and TT-TG distance (20.1 ± 4.8 mm) in the study group were significantly greater than the control group (10.6 ± 7.9° and 15.6 ± 4.6 mm, respectively) (p < 0.001). The AUCs for patellar dislocation were 0.869 for FAA and 0.712 for TT-TG distance, with pathological cut-off values of 18.2° and 18.2 mm, respectively. The odds ratios for FAA and TT-TG distance were 1.185 and 1.125, respectively (p < 0.05). CONCLUSIONS: Patients with patellar instability exhibited significantly greater FAA and TT-TG distance compared to healthy individuals. The FAA demonstrated superior predictive capability for patellar dislocation compared to the TT-TG distance. The FAA (>18.2°) measured by surgical transepicondylar axis and TT-TG distance (>18.2 mm) were the potential pathological thresholds. Additionally, an increase of 1° in FAA and 1 mm in TT-TG distance was associated with a 18.5% and 12.5% increased risk of patellar dislocation, respectively. Surgeons should be aware of the risk of patellar dislocation associated with rotational malalignment. LEVEL OF EVIDENCE: Level III.

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OBJECTIVE: As new knowledge is produced at a rapid pace in the biomedical field, existing biomedical Knowledge Graphs (KGs) cannot be manually updated in a timely manner. Previous work in Natural Language Processing (NLP) has leveraged link prediction to infer the missing knowledge in general-purpose KGs. Inspired by this, we propose to apply link prediction to existing biomedical KGs to infer missing knowledge. Although Knowledge Graph Embedding (KGE) methods are effective in link prediction tasks, they are less capable of capturing relations between communities of entities with specific attributes (Fanourakis et al., 2023). METHODS: To address this challenge, we proposed an entity distance-based method for abstracting a Community Knowledge Graph (CKG) from a simplified version of the pre-existing PubMed Knowledge Graph (PKG) (Xu et al., 2020). For link prediction on the abstracted CKG, we proposed an extension approach for the existing KGE models by linking the information in the PKG to the abstracted CKG. The applicability of this extension was proved by employing six well-known KGE models: TransE, TransH, DistMult, ComplEx, SimplE, and RotatE. Evaluation metrics including Mean Rank (MR), Mean Reciprocal Rank (MRR), and Hits@k were used to assess the link prediction performance. In addition, we presented a backtracking process that traces the results of CKG link prediction back to the PKG scale for further comparison. RESULTS: Six different CKGs were abstracted from the PKG by using embeddings of the six KGE methods. The results of link prediction in these abstracted CKGs indicate that our proposed extension can improve the existing KGE methods, achieving a top-10 accuracy of 0.69 compared to 0.5 for TransE, 0.7 compared to 0.54 for TransH, 0.67 compared to 0.6 for DistMult, 0.73 compared to 0.57 for ComplEx, 0.73 compared to 0.63 for SimplE, and 0.85 compared to 0.76 for RotatE on their CKGs, respectively. These improved performances also highlight the wide applicability of the extension approach. CONCLUSION: This study proposed novel insights into abstracting CKGs from the PKG. The extension approach indicated enhanced performance of the existing KGE methods and has applicability. As an interesting future extension, we plan to conduct link prediction for entities that are newly introduced to the PKG.

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BACKGROUND: Attribution models have been examined in Western countries. However, little is known about the applicability of the attitude-emotion-behavior model within Chinese culture. This study aimed to examine the association between familiarity, perceived dangerousness, fear, and social distance towards persons with mental illness (PMI) in the Chinese context. METHODS: An online cross-sectional survey was conducted from October to November 2022 in mainland China. A total of 1493 college students completed a questionnaire evaluating familiarity, perception of dangerousness, fear, and social distance regarding PMI. Path analysis was employed to validate the model proposed in this study. RESULTS: Participants expressed moderate to high levels of stigma towards PMI. Familiarity was negatively associated with social distance (p < 0.01). Participants who perceived PMI as dangerous were more prone to exhibit a reaction of fear (p < 0.001), consequently leading to social distance (p < 0.01). However, the mediating effect of perceived dangerousness and fear on the relationship between familiarity and social distance was not significant (p > 0.05). CONCLUSIONS: The results of this study provide support for Corrigan's attributional model of stigma in the Chinese context. Contact-based interventions for stigma reduction should emphasize multiple elements of contact, including the quality of contact, rather than familiarity.

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Hybrid-carrageenan hydrogels are characterized using novel techniques based on high-resolution speckle imaging, namely image dynamic light scattering (IDLS) and ultra-small-angle light scattering (USALS). These techniques, used to probe the microscopic structure of the system in sol-gel phase separation and at different concentrations in the gel phase, give access to a better understanding of the network's topology on the basis of fractals in the dense phase. Observations of the architecture and the spatial and the size distributions of gel phase and fractal dimension were performed by USALS. The pair-distance distribution function, P(r), extracted from USALS patterns, is a new methodology of calculus for determining the network's internal size with precision. All structural features are systematically compared with a linear and non-linear rheological characterization of the gels and structure-elasticity relationships are identified in the framework of fractal colloid gels in the diffusion limit.

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Three studies were conducted to examine the influence of moral identity on sense of humor, employing the benign violation theory (BVT) as a theoretical framework. Study 1 (n = 350), a questionnaire-based survey, aimed to establish a preliminary exploration of the relationship between moral identity and sense of humor. Studies 2 (n = 172) and 3 (n = 172) jointly examined the impact of activated moral identity on sense of humor (humor appreciation, humor sharing) through the recollection and writing task. The results of these studies indicated that the effects of (activated) moral identity on the sense of humor (humor appreciation, humor sharing) were moderated by the type of humor and social distance of the target. On the one hand, high levels of (or activated) moral identity can significantly and positively predict sense of humor (humor appreciation, sharing); on the other hand, when there is a moral violation in the humor, and the target involved is at a close social distance, activated moral identity decreases the humor appreciation and humor sharing, where benign judgment plays a mediating role. These findings enrich the understanding of the complex relationship between moral identity and sense of humor, and have significant theoretical and practical implications.

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Inter-individual distance (IID) is an important indicator of social organisation because solitary species are spatially intolerant towards conspecifics, whereas group-living species are usually gregarious with collective behaviour. Therefore, by examining the relationship between the distribution of IIDs and the active space of cues or signals, and behaviours, we can predict their social organisation. The narrow-ridged finless porpoises (NRFPs) have been described as a solitary species; however, recent studies described NRFPs tend to live in groups more than alone. To resolve the inconsistency, the present study investigated IIDs, the active spaces of sounds, and behaviours. The distribution of IIDs measured using drone was classified into three distributions. The close and intermediate distributions were significantly shorter than the distribution predicted by the angle of drone camera, whereas the far distributions were not. The far distributions were thus a random distribution within the limited angle of the camera. The close distributions were shorter than the active space, exhibiting a high proportion of collective behaviours, while intermediate distributions did not. These results suggest that NRFPs have both solitary- and group-living characteristics. Specifically, the intermediate distribution suggests a solitary aspect to maintain IIDs from others, while the close distribution indicates a group-living aspect with social interactions.