Ketosis, especially its subclinical form, is frequently observed in high-yielding dairy cows and is linked to various diseases during the transition period. Although adipose tissue plays a significant role in the development of metabolic disorders, its exact impact on the emergence of subclinical ketosis (SCK) is still poorly understood. The objectives of this study were to characterize and compare the profiling of transcriptome and lipidome of blood and adipose tissue between SCK and healthy cows and investigate the potential correlation between metabolic disorders and lipid metabolism. We obtained blood and adipose tissue samples from healthy cows (CON, n = 8, β-hydroxybutyric acid concentration < 1.2 mmol/L) and subclinical ketotic cows (SCK, n = 8, β-hydroxybutyric acid concentration = 1.2–3.0 mmol/L) for analyzing biochemical parameters, transcriptome, and lipidome. We found that serum levels of nonesterified fatty acids, malonaldehyde, serum amyloid A protein, IL-1β, and IL-6 were higher in SCK cows than in CON cows. Levels of adiponectin and total antioxidant capacity were higher in serum and adipose tissue from SCK cows than in CON cows. The top enriched pathways in whole blood and adipose tissue were associated with immune and inflammatory responses and sphingolipid metabolism, respectively. The accumulation of ceramide and sphingomyelin in adipose tissue was paralleled by an increase in genes related to ceramide biosynthesis, lipolysis, and inflammation and a decrease in genes related to ceramide catabolism, lipogenesis, adiponectin production, and antioxidant enzyme systems. Increased ceramide concentrations in blood and adipose tissue correlated with reduced insulin sensitivity. The current results indicate that the lipid profile of blood and adipose tissue is altered with SCK and that certain ceramide species correlate with metabolic health. Our research suggests that disruptions in ceramide metabolism could be crucial in the progression of SCK, exacerbating conditions such as insulin resistance, increased lipolysis, inflammation, and oxidative stress, providing a potential biomarker of SCK and a novel target for nutritional manipulation and pharmacological therapy. Full article

For the vibration of automobile powertrain, this paper designs electro–hydraulic composite engine mounts. Subsequently, the dynamic characteristics of the hydraulic mount and the electromagnetic actuator were analyzed and experimentally studied separately. Due to the strong nonlinearity of the hybrid electromechanical engine mount, a Fractional-Order Least-Mean-Square (FGO-LMS) algorithm was proposed to model its secondary path identification. To validate the vibration reduction effect, a rapid control prototype test platform was established, and vibration active control experiments were conducted based on the Multiple–Input Multiple–Output Filter-x Least-Mean-Square (MIMO-FxLMS) algorithm. The results indicate that, under various operating conditions, the vibration transmitted to the chassis from the powertrain was significantly suppressed. Full article

The tumor microenvironment (TME) can aid tumor cells in evading surveillance and clearance by immune cells, creating an internal environment conducive to tumor cell growth. Consequently, there is a growing focus on researching anti-tumor immunity through the regulation of immune cells within the TME. Various bioactive compounds in traditional Chinese medicine (TCM) are known to alter the immune balance by modulating the activity of immune cells in the TME. In turn, this enhances the body’s immune response, thus promoting the effective elimination of tumor cells. This study aims to consolidate recent findings on the regulatory effects of bioactive compounds from TCM on immune cells within the TME. The bioactive compounds of TCM regulate the TME by modulating macrophages, dendritic cells, natural killer cells and T lymphocytes and their immune checkpoints. TCM has a long history of having been used in clinical practice in China. Chinese medicine contains various chemical constituents, including alkaloids, polysaccharides, saponins and flavonoids. These components activate various immune cells, thereby improving systemic functions and maintaining overall health. In this review, recent progress in relation to bioactive compounds derived from TCM will be covered, including TCM alkaloids, polysaccharides, saponins and flavonoids. This study provides a basis for further in-depth research and development in the field of anti-tumor immunomodulation using bioactive compounds from TCM. Full article

The gut microbiota plays a crucial role in the host’s metabolic processes. Many studies have shown significant changes in the gut microbiota of mammals during hibernation to adapt to the changes in the external environment, but there is limited research on the colonic epithelial tissue and gut microbiota of the wild chipmunks during hibernation. This study analyzed the diversity, composition, and function of the gut microbiota of the wild chipmunk during hibernation using 16S rRNA gene high-throughput sequencing technology, and further conducted histological analysis of the colon. Histological analysis of the colon showed an increase in goblet cells in the hibernation group, which was an adaptive change to long-term fasting during hibernation. The dominant gut microbial phyla were Bacteroidetes, Firmicutes, and Proteobacteria, and the relative abundance of them changed significantly. The analysis of gut microbiota structural differences indicated that the relative abundance of Helicobacter typhlonius and Mucispirillum schaedleri increased significantly, while unclassified Prevotella-9, unclassified Prevotellaceae-UCG-001, unclassified Prevotellaceae-UCG-003 and other species of Prevotella decreased significantly at the species level. Alpha diversity analysis showed that hibernation increased the diversity and richness of the gut microbiota. Beta diversity analysis revealed significant differences in gut microbiota diversity between the hibernation group and the control group. PICRUSt2 functional prediction analysis of the gut microbiota showed that 15 pathways, such as lipid metabolism, xenobiotics biodegradation and metabolism, amino acid metabolism, environmental adaptation, and neurodegenerative diseases, were significantly enriched in the hibernation group, while 12 pathways, including carbohydrate metabolism, replication and repair, translation, and transcription, were significantly enriched in the control group. It can be seen that during hibernation, the gut microbiota of the wild chipmunk changes towards taxa that are beneficial for reducing carbohydrate consumption, increasing fat consumption, and adapting more strongly to environmental changes in order to better provide energy for the body and ensure normal life activities during hibernation. Full article

Considering the escalating resistance to conventional antifungal medications, it is critical to identify novel compounds that can efficiently counteract this challenge. The purpose of this research was to elucidate the fungicidal properties of secondary metabolites derived from Arcangelisia flava, with a specific focus on their efficacy against Candida species. This study utilized a combination approach comprising laboratory simulations and experiments to discern and evaluate the biologically active constituents present in the dichloromethane extract of A. flava. The in vitro experiments demonstrated that compounds 1 (palmatine) and 2 (fibraurin) exhibited antifungal properties. The compounds exhibited minimum inhibitory concentrations (MICs) ranging from 15.62 to 62.5 µg/mL against Candida sp. Moreover, compound 1 demonstrated a minimum fungicidal concentration (MFC) of 62.5 µg/mL against Candida glabrata and C. krusei. In contrast, compound 2 exhibited an MFC of 125 µg/mL against both Candida species. Based on a molecular docking study, it was shown that compounds 1 and 2 have a binding free energy of −6.6377 and −6.7075 kcal/mol, respectively, which indicates a strong affinity and specificity for fungal enzymatic targets. This study utilized pharmacophore modeling and Density Functional Theory (DFT) simulations to better understand the interaction dynamics and structural properties crucial for antifungal activity. The findings underscore the potential of secondary metabolites derived from A. flava to act as a foundation for creating novel and highly efficient antifungal treatments, specifically targeting fungal diseases resistant to existing treatment methods. Thus, the results regarding these compounds can provide references for the next stage in antifungal drug design. Further investigation is necessary to thoroughly evaluate these natural substances’ clinical feasibility and safety characteristics, which show great potential as antifungal agents. Full article

As artificial intelligence (AI) integrates within the intersecting domains of healthcare and computational biology, developing interpretable models tailored to medical contexts is met with significant challenges. Explainable AI (XAI) is vital for fostering trust and enabling effective use of AI in healthcare, particularly in image-based specialties such as pathology and radiology where adjunctive AI solutions for diagnostic image analysis are increasingly utilized. Overcoming these challenges necessitates interdisciplinary collaboration, essential for advancing XAI to enhance patient care. This commentary underscores the critical role of interdisciplinary conferences in promoting the necessary cross-disciplinary exchange for XAI innovation. A literature review was conducted to identify key challenges, best practices, and case studies related to interdisciplinary collaboration for XAI in healthcare. The distinctive contributions of specialized conferences in fostering dialogue, driving innovation, and influencing research directions were scrutinized. Best practices and recommendations for fostering collaboration, organizing conferences, and achieving targeted XAI solutions were adapted from the literature. By enabling crucial collaborative junctures that drive XAI progress, interdisciplinary conferences integrate diverse insights to produce new ideas, identify knowledge gaps, crystallize solutions, and spur long-term partnerships that generate high-impact research. Thoughtful structuring of these events, such as including sessions focused on theoretical foundations, real-world applications, and standardized evaluation, along with ample networking opportunities, is key to directing varied expertise toward overcoming core challenges. Successful collaborations depend on building mutual understanding and respect, clear communication, defined roles, and a shared commitment to the ethical development of robust, interpretable models. Specialized conferences are essential to shape the future of explainable AI and computational biology, contributing to improved patient outcomes and healthcare innovations. Recognizing the catalytic power of this collaborative model is key to accelerating the innovation and implementation of interpretable AI in medicine. Full article

Red yeast rice dietary supplements have been proven to ameliorate hyperglycemia, but the mechanism was unclear. In this work, ankaflavin (AK) and monascin (MS), as typical pigments derived from red yeast rice, were found to exert noteworthy inhibitory ability against α-glucosidase, with an IC₅₀ of 126.5 ± 2.5 and 302.6 ± 2.5 μM, respectively, compared with acarbose (IC₅₀ = 341.3 ± 13.6 μM). They also exhibited mixed-type inhibition of α-glucosidase in vitro and caused fluorescence quenching through the static-quenching process. Molecular-docking studies indicated that AK and MS bind to amino acid residues outside the catalytic center, which induces structural changes in the enzyme, thus influencing its catalytic activity. The anti-glycation ability of Monascus-fermented products was evaluated, and they exhibited a high inhibition rate of 87.1% in fluorescent advanced glycation end-product formation at a concentration of 0.2 mg mL⁻¹, while aminoguanidine showed a rate of 75.7% at the same concentration. These results will be significant in broadening the application scope of Monascus pigments, especially AK and MS, in treating type 2 diabetes. Full article

Maintaining sufficient levels of plant nutrients in the soil and controlling certain heavy metals, which can be toxic to the environment, are critical to ensure sustainable agricultural production. The study aimed to assess the linkage of crop-specific agricultural practices established by farmers in the Kvemo Kartli region (Georgia) with metal accumulation in soils of agricultural lands being subject to influence from polluted irrigation water in the past. In particular, we tried to identify the primary sources of micro-nutrients, including iron (Fe), copper (Cu), manganese (Mn), nickel (Ni), and zinc (Zn), and toxic elements such as cadmium (Cd) and lead (Pb), and the share of the contaminated irrigation water and other factors related to agricultural practices under different land uses, such as intensive and extensive arable farming, vineyards, orchards, and permanent pastures having the least disturbed soil. Based on principal component analysis, five primary sources were identified and categorized according to farmer interviews and previous studies conducted in the region. The results showed that increased concentrations of plant-available Cu, Zn, Cd, and Pb were mainly associated with irrigation water and intensive use of fungicides; Fe, Mn, and Ni were closely linked to several factors, such as the mineralogical composition of soils, minerals, and organic fertilizers inputs; and atmospheric deposition from diffuse sources, where exhausts from transport are probably the primary source. During our study, we attempted to differentiate irrigation water inputs from fungicides using simulation based on irrigation patterns and irrigation water quality on the one hand and fungicide application rates and their metal contents on the other. The simulation revealed that the intensive application of fungicides, especially in vineyards, is more significant in enriching soils with Cu and Zn than irrigation water. Identification of factorial dependences was supported by statistical analysis and application of several contamination assessment methods: contamination factor (CF), pollution load index (PLI), single-factor pollution index (PI), Nemerow’s comprehensive pollution index (PIN), enrichment factor (EF), and geo-accumulation index (Igeo). Applied environmental indices indicate that the soils under the former and existing vineyards are the most enriched with Cu and Zn, highlighting the significance of agricultural practices on heavy metal accumulations in the soils of agricultural lands. Full article

(1) Background: Social isolation, which has numerous adverse effects on health status, is prevalent among cancer patients. This review proposes to identify the influencing factors of social isolation among cancer patients. (2) Methods: Articles published in English or Chinese from six electronic databases before December 2023 were identified via a systematic search. A manual search was also performed. (3) Results: Twenty-eight studies were identified in this systematic review. The factors associated with social isolation can be summarized into the following categories: demographic characteristics, having cancer, health status, coping, social support and social interaction. Despite the heterogeneity, 20 factors were significantly associated with social isolation, including age, gender, comorbidity burden, education level, residence, medical insurance, occupation status, personality, race, smoking status, having children, not living alone, household income level, marital status, the role of primary caregiver, physical health status, mental health status, social health status, coping styles, and the level of social support and social interaction. (4) Conclusions: The systematic review showed that cancer patients’ social isolation was influenced by their demographic characteristics, cancer-related factors, physical condition, psychological status, social health status, coping styles, and level of social support and social interaction. In addition, future group intervention could be considered to improve social isolation. Full article

Background: Flatfeet in children are common, causing concern for parents due to potential symptoms. Technological advances, like 3D foot kinematic analysis, have revolutionized assessment. This review examined 3D assessments in paediatric idiopathic flexible flat feet (FFF). Methods: Searches focused on paediatric idiopathic FFF in PubMed, Web of Science, and SCOPUS. Inclusion criteria required 3D kinematic and/or kinetic analysis during posture or locomotion, excluding non-idiopathic cases, adult feet, and studies solely on pedobarography or radiographs. Results: Twenty-four studies met the criteria. Kinematic and kinetic differences between FFF and typical feet during gait were outlined, with frontal plane deviations like hindfoot eversion and forefoot supination, alongside decreased second peak vertical GRF. Dynamic foot classification surpassed static assessments, revealing varied movement patterns within FFF. Associations between gait characteristics and clinical measures like pain symptoms and quality of life were explored. Interventions varied, with orthoses reducing ankle eversion and knee and hip abductor moments during gait, while arthroereisis normalized calcaneal alignment and hindfoot eversion. Conclusions: This review synthesises research on 3D kinematics and kinetics in paediatric idiopathic FFF, offering insights for intervention strategies and further research. Full article

To address the issue of insufficient deep contextual information mining in the semantic segmentation task of multiple defects in concrete bridges, due to the diversity in texture, shape, and scale of the defects as well as significant differences in the background, we propose the Concrete Bridge Apparent Multi-Defect Segmentation Network (PID-MHENet) based on a PID encoder and multi-feature fusion. PID-MHENet consists of a PID encoder, skip connection, and decoder. The PID encoder adopts a multi-branch structure, including an integral branch and a proportional branch with a “thick and long” design principle and a differential branch with a “thin and short” design principle. The PID Aggregation Enhancement (PAE) combines the detail information of the proportional branch and the semantic information of the differential branch to enhance the fusion of contextual information and, at the same time, introduces the self-learning parameters, which can effectively extract the information of the boundary details of the lesions, the texture, and the background differences. The Multi-Feature Fusion Enhancement Decoding Block (MFEDB) in the decoding stage enhances the information and globally fuses the different feature maps introduced by the three-channel skip connection, which improves the segmentation accuracy of the network for the background similarity and the micro-defects. The experimental results show that the mean Pixel accuracy (mPa) and mean Intersection over Union (mIoU) values of PID-MHENet on the concrete bridge multi-defect semantic segmentation dataset improved by 5.17% and 5.46%, respectively, compared to the UNet network. Full article

Throughout the last decade, chatbots have gained widespread adoption across various industries, including healthcare, education, business, e-commerce, and entertainment. These types of artificial, usually cloud-based, agents have also been used in airport customer service, although there has been limited research concerning travelers’ perspectives on this rather techno-centric approach to handling inquiries. Consequently, the goal of the presented study was to tackle this research gap and explore potential use cases for chatbots at airports, as well as investigate travelers’ acceptance of said technology. We employed an extended version of the Technology Acceptance Model considering Perceived Usefulness, Perceived Ease of Use, Trust, and Perceived Enjoyment as predictors of Behavioral Intention, with Affinity for Technology as a potential moderator. A total of $n=191$ travelers completed our survey. The results show that Perceived Usefulness, Trust, Perceived Ease of Use, and Perceived Enjoyment positively correlate with the Behavioral Intention to use a chatbot for airport customer service inquiries, with Perceived Usefulness showing the highest impact. Travelers’ Affinity for Technology, on the other hand, does not seem to have any significant effect. Full article

Internal combustion engines have been a major contributor to air pollution. Replacing these engines with electric propulsion systems presents significant challenges due to different countries’ needs and limitations. An active, purely mechanical solution to the problem of irregular torque production in an alternative internal combustion engine is proposed. This solution uses an actuator built on a camshaft and a spring, which stores and returns energy during the engine operating cycle, allowing torque production to be normalized, avoiding heavy flywheels. Designed for control throughout the engine’s duty cycle, this system incorporates a cam profile and a spring mechanism. The spring captures energy during the expansion stroke, which is then released to the engine during the intake and compression strokes. Simple, lightweight, and efficient, this system ensures smoother and more consistent engine operations. It presents a viable alternative to the heavy and problematic dual-mass flywheels that were introduced in the 1980s and are still in use. This innovative approach could significantly enhance the performance and reliability of alternative internal combustion engines without notable energy losses. Full article

Dissolved gases in the aquatic environment are critical to understanding the population of aquatic organisms and the ocean. Currently, laser absorption techniques based on membrane separation technology have made great strides in dissolved gas detection. However, the prolonged water–gas separation time of permeable membranes remains a key obstacle to the efficiency of dissolved gas analysis. To mitigate these limitations, we demonstrated direct measurement of dissolved gas using the evanescent-wave absorption spectroscopy of a tapered silica micro-fiber. It enhanced the analysis efficiency of dissolved gases without water–gas separation or sample preparation. The feasibility of this sensor for direct measurement of dissolved gases was verified by taking the detection of dissolved ammonia as an example. With a sensing length of 5 mm and a consumption of ~50 µL, this sensor achieves a system response time of ~11 min and a minimum detection limit (MDL) of 0.015%. Possible strategies are discussed for further performance improvement in in-situ applications requiring fast and highly sensitive dissolved gas sensing. Full article

Predictive maintenance (PdM) is one of the most powerful maintenance techniques based on the estimation of the remaining useful life (RUL) of machines. Accurately estimating the RUL is crucial to ensure the effectiveness of PdM. However, current methods have limitations in fully exploring condition monitoring data, particularly vibration signals, for RUL estimation. To address these challenges, this research presents a novel Robust Multi-Branch Deep Learning (Robust-MBDL) model. Robust-MBDL stands out by leveraging diverse data sources, including raw vibration signals, time–frequency representations, and multiple feature domains. To achieve this, it adopts a specialized three-branch architecture inspired by efficient network designs. The model seamlessly integrates information from these branches using an advanced attention-based Bi-LSTM network. Furthermore, recognizing the importance of data quality, Robust-MBDL incorporates an unsupervised LSTM-Autoencoder for noise reduction in raw vibration data. This comprehensive approach not only overcomes the limitations of existing methods but also leads to superior performance. Experimental evaluations on benchmark datasets such as XJTU-SY and PRONOSTIA showcase Robust-MBDL’s efficacy, particularly in rotating machine health prognostics. These results underscore its potential for real-world applications, heralding a new era in predictive maintenance practices. Full article

Pancreatic pseudocysts often arise as complications of pancreatitis and present unique challenges in clinical management, encompassing considerations for both technical aspects and financial implications. Before the advancements of invasive gastroenterology, pancreatic pseudocysts have been drained surgically for many years. Nowadays, we have less invasive techniques with higher efficiency and lower mortality rates, however, they remain cost-challenging for most countries. Materials and Methods: We present four patients (two males and two females) with pancreatic pseudocysts who underwent endoscopic ultrasound-guided transgastric drainage using plastic stents accompanied by a standard lavage protocol using a nasocystic catheter. Results: All four patients had successful outcomes, and a follow-up at 6 months revealed no traces of the pseudocysts or any significant long-term complications. One acute complication (arterial bleeding) and one late complication (stent migration) were observed. As the study aimed to present a cheaper option for draining pancreatic pseudocysts, we investigated and compared costs for the materials we utilized and those associated with lumen-apposing metal stents. Upon compiling the data, a notable advantage was evident in favour of our method. Conclusions: While EUS-guided drainage of pancreatic pseudocysts using lumen-apposing metal stents (LAMSs) represents a high-end strategy for treating pancreatic pseudocysts, our method demonstrates better cost-effectiveness without compromising efficacy. Full article

Various studies have shown that Hypogymnia physodes are a source of many biologically active compounds, including lichen acids. These lichen-specific compounds are characterized by antioxidant, antiproliferative, and antimicrobial properties, and they can be used in the cosmetic and pharmaceutical industries. The main aim of this study was to optimize the composition of natural deep eutectic solvents based on proline or betaine and lactic acid for the extraction of metabolites from H. physodes. The design of the experimental method and the response surface approach allowed the optimization of the extraction process of specific lichen metabolites. Based on preliminary research, a multivariate model of the experiment was developed. For optimization, the following parameters were employed in the experiment to confirm the model: a proline/lactic acid/water molar ratio of 1:2:2. Such a mixture allowed the efficient extraction of three depsidones (i.e., physodic acid, physodalic acid, 3-hydroyphysodic acid) and one depside (i.e., atranorin). The developed composition of the solvent mixtures ensured good efficiency when extracting the metabolites from the thallus of H. physodes with high antioxidant properties. Full article

Fish oils are widely consumed around the world to increase omega-3 fatty acid intake. Due to negative impacts on marine resources and ecosystems from an increasing demand for fish, alternative sustainable sources are under investigation. Squid viscera contains up to 10% oil by mass and is available as a byproduct from squid processing. Squid viscera oil is a source of EPA and DHA and contains the xanthophyll carotenoid astaxanthin, known for its significant anticancer, antioxidant, antidiabetic, and cardiovascular properties. In the raw form, squid viscera oil has a high free fatty acid (FFA) content, so conventional alkaline refining results in low yield and loss of astaxanthin. As a higher-yielding alternative, the current study optimized lipase-catalyzed glycerolysis of squid viscera oil to convert FFA into acylglycerol using a custom-built one-liter immobilized enzyme reactor. To monitor the reaction progress and assess its impact on the oil, we analyzed lipid classes, fatty acid composition and astaxanthin levels. Under optimized conditions, FFA was reduced from 40% to 2.7% in 10 h and 1.7% in 24 h, with no significant effect on EPA and DHA levels, and astaxanthin being retained. Squid viscera presents a safe and sustainable additional source of marine-derived EPA and DHA oil. Full article

Poly(2-hydroxyethylmethacrylate-co-2-(dimethylamino)ethyl methacrylate), P(HEMA-co-DMAEMAx), copolymers were quaternized through the reaction of a part of (dimethylamino)ethyl moieties of DMAEMA units with 1-bromohexadecane. Antimicrobial coatings were further prepared through the cross-linking reaction between the remaining DMAEMA units of these copolymers and the epoxide ring of poly(N,N-dimethylacrylamide-co-glycidyl methacrylate), P(DMAm-co-GMAx), copolymers. The combination of P(HEMA-co-DMAEMAx)/P(DMAm-co-GMAx) copolymers not only enabled control over quaternization and cross-linking for coating stabilization but also allowed the optimization of the processing routes towards a more facile cost-effective methodology and the use of environmentally friendly solvents like ethanol. Careful consideration was given to achieve the right content of quaternized units, qDMAEMA, to ensure antimicrobial efficacy through an appropriate amphiphilic balance and sufficient free DMAEMA groups to react with GMA for coating stabilization. Optimal synthesis conditions were achieved by membranes consisting of cross-linked P(HEMA78-co-DMAEMA9-co-qDMAEMA13)/P(DMAm-co-GMA42) membranes. The obtained membranes were multifunctional as they were self-standing and antimicrobial, while they demonstrated a distinct fast response to changes in humidity levels, widening the opportunities for the construction of “smart” antimicrobial actuators, such as non-contact antimicrobial switches. Full article

The diagnosis of a child’s complex chronic illness may impact family relationships and cohesion. The Impact on Family Scale (IFS) is an instrument used to assess the parental perception of the effects of children’s chronic illness on family life. With a sample of 110 mothers and fathers between the ages of 29 and 50 who have a child with a complex chronic illness, we examine evidence of the validity of the IFS for use in Portugal within this specific family configuration, (1) comparing its factor structure with the original one; (2) assessing its reliability; and (3) evaluating its relationship with life satisfaction and family cohesion/acceptance. As expected, CFA analysis showed that IFS is a one-factor reliable instrument with 12 items (Cronbach’s alpha = 0.910), which are negatively correlated with satisfaction with life (r = −0.229, p = 0.016) and positively correlated with family acceptance and cohesion (r = 0.363; p < 0.001). The results support the validity of the IFS in families with children and adolescents with a complex chronic illness. The implications of the use of this instrument for research and professional practice is analyzed. Full article

Video classification is a challenging task in computer vision that requires analyzing the content of a video to assign it to one or more predefined categories. However, due to the vast amount of visual data contained in videos, the classification process is often computationally expensive and requires a significant amount of annotated data. Because of these reasons, the low-data-based video classification area, which consists of few-shot and zero-shot tasks, is proposed as a potential solution to overcome traditional video classification-oriented challenges. However, existing low-data area datasets, which are either not diverse or have no additional modality context, which is a mandatory requirement for the zero-shot task, do not fulfill the requirements for few-shot and zero-shot tasks completely. To address this gap, in this paper, we propose a large-scale, general-purpose dataset for the problem of multi-modal low-data-based video classification. The dataset contains pairs of videos and attributes that capture multiple facets of the video content. Thus, the new proposed dataset will both enable the study of low-data-based video classification tasks and provide consistency in terms of comparing the evaluations of future studies in this field. Furthermore, to evaluate and provide a baseline for future works on our new proposed dataset, we present a variational autoencoder-based model that leverages the inherent correlation among different modalities to learn more informative representations. In addition, we introduce a regularization technique to improve the baseline model’s generalization performance in low-data scenarios. Our experimental results reveal that our proposed baseline model, with the aid of this regularization technique, achieves over 12% improvement in classification accuracy compared to the pure baseline model with only a single labeled sample. Full article

While children have experienced less severe coronavirus disease (COVID-19) after SARS-CoV-2 infection than adults, the cause of this remains unclear. The objective of this study was to describe the humoral immune response to COVID-19 in child vs. adult household contacts, and to identify predictors of the response over time. In this prospective cohort study, children with a positive SARS-CoV-2 polymerase chain reaction (PCR) test (index case) were recruited along with their adult household contacts. Serum IgG antibodies against SARS-CoV-2 S1/S2 spike proteins were compared between children and adults at 6 and 12 months after infection. A total of 91 participants (37 adults and 54 children) from 36 families were enrolled. Overall, 78 (85.7%) participants were seropositive for anti-S1/S2 IgG antibody at 6 months following infection; this was higher in children than in adults (92.6% vs. 75.7%) (p = 0.05). Significant predictors of a lack of SARS-CoV-2 seropositivity were age ≥ 25 vs. < 12 years (odds ratio [OR] = 0.23, p = 0.04), presence of comorbidities (vs. none, adjusted OR = 0.23, p = 0.03), and immunosuppression (vs. immunocompetent, adjusted OR = 0.17, p = 0.02). Full article