Powdered products for dysphagia are often discussed primarily in clinical terms, yet their performance depends on how texture develops during reconstitution and oral processing. In these systems, wetting, dispersion, hydration, hydrocolloid-matrix interactions, resting time, temperature, and salivary exposure jointly determine whether the prepared bolus will be homogeneous, stable, and functionally appropriate at the time of swallowing. This critical integrative review examines powdered foods for dysphagia from a texture design perspective and brings together evidence on the clinical management of dysphagia, IDDSI implementation, shear and extensional rheology, tribology, powder architecture, and reconstitution science. Electronic searches were conducted in PubMed/MEDLINE, Scopus, Web of Science, and ScienceDirect, with backward and forward citation tracking to capture seminal and recent studies. Taken together, the literature shows that liquids classified within the same IDDSI level may differ materially in flow curve profile, viscoelastic recovery, lubrication, and sensory load, whereas studies on powders show that particle size, agglomeration, porosity, surface composition, solids loading, and mixing protocol govern wetting, dispersion, and structural uniformity. In nutrient-dense matrices, such as systems containing cocoa, dairy ingredients, and fibers, thickener performance is matrix- and time-dependent; therefore, the same nominal thickener dose does not guarantee equivalent oral behavior across different products. The reviewed evidence supports a formulation-driven development agenda in which powder architecture, hydrocolloid choice, preparation instructions, and functional texture verification are optimized in an integrated way. Reconstitutable powders are not inherently superior to ready-to-use products, but they may provide a promising platform for standardization, logistical flexibility, and nutritional densification when reconstitution and oral texture are treated as parts of the same system.
Pleomorphic adenoma (PA) and Warthin tumor (WT) are the two most common benign parotid tumors, and their distinct management strategies necessitate accurate preoperative discrimination. Therefore, this study aimed to investigate the value of ultrasound texture analysis in differentiating between them. This retrospective study analyzed ultrasound images from patients with pathologically confirmed PA or WT. Following lesion segmentation, texture features were extracted from the regions of interest (ROI). Feature selection was subsequently performed to identify the most discriminative feature subset. Machine learning (ML) models were constructed based on the selected features and evaluated on an independent test set using metrics including accuracy, sensitivity, specificity, and the area under the curve (AUC). Finally, SHapley Additive exPlanations (SHAP) was employed to interpret the model's predictions and quantify the contribution of key features, thereby linking them to sonographic characteristics of the tumors. In addition, the cut-off value of each feature was calculated. Eight key texture features were identified. PA showed more homogeneous and regular patterns, whereas WT appeared more heterogeneous and random. A discriminative model using these features achieved good performance on the test set: AUC 0.958 [95% confidence interval (CI): 0.899-0.996], sensitivity 90.5% (95% CI: 76.9-100.0%), specificity 83.3% (95% CI: 66.7-96.3%). On the independent external validation cohort, the model achieved accuracy 85.4% (95% CI: 73.2-95.1%), sensitivity 72.2% (95% CI: 50.0-92.9%), specificity 95.7% (95% CI: 86.4-100.0%), and AUC 82.4% (95% CI: 67.7-95.7%). This study identified and validated eight texture features that may help distinguish PA from WT in the parotid gland. Integrated into an ML model, these features showed discriminative potential, offering a useful adjunct for preoperative assessment of parotid masses.
Early hematoma expansion is a major determinant of poor outcome in hypertensive basal ganglia hemorrhage. This study evaluated whether CT-based radiomic texture analysis could improve early prediction of hematoma expansion. A retrospective cohort of 104 patients with hypertensive basal ganglia hemorrhage who underwent baselinef CT within 6 h of symptom onset and follow-up CT within 48 h was analyzed. Hematoma regions of interest were manually segmented, and 256 texture features were extracted using MaZda. Fisher's score, probability of error and average correlation coefficient, and mutual information were used for dimensionality reduction. Classification performance was assessed using raw data analysis, principal component analysis, linear discriminant analysis, and nonlinear discriminant analysis, followed by ROC analysis. Hematoma expansion occurred in 40 of 104 patients (38.4 %). Nonlinear discriminant analysis showed the lowest misclassification rate overall, including 0 under the POE-ACC feature set. ROC analysis demonstrated good diagnostic performance for several texture features, with S(3, -3)Difvarnc (AUC 0.944), S(4, -4)Difvarnc (AUC 0.942), and GrVariance (AUC 0.917) showing the strongest predictive value. CT-based texture analysis provides quantitative imaging biomarkers that may support early risk stratification of hematoma expansion in basal ganglia hemorrhage.
Chiral spin textures, such as spin spirals and skyrmions, are key to advancing spintronics by enabling ultrathin, energy-efficient memory, and high-density data storage and processing. However, their realization remains hindered by the scarcity of suitable host materials and the formidable experimental challenges associated with the characterization of these intricate chiral magnetic states. Here, we report the observation of tunable chiral magnetic textures in van der Waals magnet CrPS4 with nonlinear optics. These tunable textures exhibit strong chiral third-order nonlinear optical responses, driven by interlayer and intralayer spin couplings under varying magnetic fields and temperatures. These pronounced chiral nonlinear optical responses highlight the potency and high sensitivity of the nonlinear optical readout for probing non-collinear magnetic orders. Moreover, our findings position van der Waals magnets and their heterostructures as an exceptional platform for reconfigurable spin-photonics and spintronics, unifying optical, electrical, and magnetic properties through unique intralayer and interlayer spin coupling properties and effective spin interaction between photons and electrons.
This study evaluated the potential of Moringa oleifera seed rennet (MSR) as a novel hydrocolloid coagulant for mozzarella cheese production compared with commercial rennets. Mozzarella cheeses were manufactured using MSR and 3 commercial rennets (calf rennet, CR, papain rennet, PR, rice black mold rennet, MR). MSR-treated cheese (MSRC) showed comparable nutritional value to calf rennet cheese (CRC), with no significant differences in protein and fat content (P > 0.05), while exhibiting superior hardness and elasticity compared with PR- and MR-treated cheeses.Mechanistically, MSR specifically hydrolyzed κ-casein, increasing α-helix content and fluorescence intensity while reducing free sulfhydryl content, indicating strengthened protein secondary and tertiary structures. These changes led to a denser, more stable protein gel network with smaller pore sizes and more uniform casein distribution, as confirmed by microstructure analysis. Rheologically, MSRC exhibited higher G' and G" values, indicating enhanced elastic and viscous gel-like behavior. Correlation analysis revealed strong positive correlations between fat content and hardness (r = 0.995) and between protein content and elasticity (r = 0.951), while α-helix structure was negatively correlated with moisture (r = -0.980), resilience (r = -0.915), and meltability (r = -0.880). These findings demonstrate that MSR is a viable plant-based, sustainable alternative to commercial rennets for mozzarella cheese production.
Low-dose computed tomography (LDCT) is widely used to reduce radiation exposure, but the reduced photon budget amplifies quantum noise and can introduce structured artifacts that obscure subtle boundaries and textures. Many deep learning denoisers process features in a single stream, which may encourage either over-smoothing of weak anatomical edges or unstable texture synthesis. To develop an LDCT denoising network that explicitly routes coarse structural content and fine details through dedicated pathways, aiming to suppress noise while preserving anatomically meaningful high-frequency information. We propose FMDNet, a frequency-aware encoder-decoder equipped with an explicit coarse/detail routing block. A fixed low-pass operator produces a coarse component, while the corresponding detail component is formed as an explicit residual (high = x-low). Each component is refined with depthwise operators and fused by a learned channel gate with channel attention. We evaluate FMDNet on the AAPM Mayo Clinic LDCT dataset and the LoDoPaB-CT benchmark under a reproducible HU-windowed protocol and supplement PSNR, SSIM, and RMSE with texture- and structure-oriented analyses including HU line profiles and noise power spectrum (NPS), together with volume-level paired tests and bootstrap confidence intervals on LoDoPaB-CT. Across both benchmarks, FMDNet achieves competitive quantitative fidelity and shows favorable results on complementary structure-/texture-oriented analyses. On Mayo, it improves mean PSNR, SSIM, and RMSE relative to strong learned baselines. On LoDoPaB-CT, volume-level analysis across 28 validation volumes confirms consistent improvements over Uformer with paired tests and bootstrap confidence intervals. Additional HU-profile and NPS analyses provide complementary evidence of improved texture preservation and local structural fidelity relative to comparative methods. Explicitly separating coarse and detail residual components in feature space provides a practical inductive bias for LDCT denoising. When combined with gated fusion and multi-scale supervision, this strategy improves quantitative fidelity and preserves fine structures without relying on adversarial texture synthesis; clinical diagnostic impact should be validated by reader studies.
Slip-related accidents remain a significant safety concern in public walkways, healthcare facilities, and industrial environments, particularly under contaminated surface conditions. Although numerous studies have investigated slip resistance using friction measurements and statistical classification approaches, existing predictive models often rely on simplified linear relationships or data-driven algorithms that provide limited physical interpretability of tribological interactions. This study aims to experimentally evaluate the slip-resistance performance of coated ceramic walkway surfaces under varying environmental conditions and to develop an interpretable, nonlinear, predictive framework, termed TexCoMP (Texture-Coating-Material-Performance), that integrates coating properties, surface texture characteristics, and environmental contamination effects. Specific objectives are to: (1) compare four coatings across four ceramic tiles and three shoe types; (2) assess arid, damp, and foamy environmental impacts; and (3) identify optimal combinations for walkway safety per ANSI A137.1:2022 and ISO 5436:2021 standards. Four coating materials (CM 1-CM 4) were applied to four ceramic tile surfaces (CT 1-CT 4) and evaluated using tribological testing under arid, damp, and foamy contamination conditions with three footwear materials. Surface texture parameters were characterised using roughness measurements, and dynamic friction coefficients (DFCs) were determined through controlled dynamic friction tests. A nonlinear predictive model incorporating coating material performance (CMP), surface texture modification (STM), and environmental factors (E) was developed and validated using statistical analysis and cross-validation across 144 experimental combinations (432 individual measurements). TexCoMP achieved a mean absolute error (MAE) of 0.03, a root mean square error (RMSE) of 0.04, a Pearson correlation (R) of 0.92, and an R2 of 0.93, outperforming linear models by 22% in terms of RMSE under foamy conditions. The epoxy-CT4 pairing yielded a DFC of 0.62 ± 0.03 in damp conditions, 24% above the OSHA safety threshold of 0.5, indicating substantially reduced slip potential. Four-way ANOVA revealed highly significant interactions (p < 0.001) with environmental condition as the dominant factor (partial η² = 0.47). The proposed TexCoMP framework provides an interpretable tribological model for predicting slip resistance in coated walkway systems by integrating coating material properties, surface texture modification, and environmental contamination effects. The results demonstrate that coatings incorporating texture-enhancing particles can significantly improve friction performance under damp conditions. TexCoMP therefore offers a practical analytical tool for guiding coating selection and surface engineering strategies to reduce slip-related risks in built environments.
Breast cancer is a heterogeneous disease whose molecular subtypes differ in biological behavior, prognosis, and therapeutic response. This study investigated whether whole-breast radiomic features extracted from digital mammograms and showing statistically significant differences between HER2 + tumors and other molecular subtypes or healthy controls could also provide discriminatory information for exploratory HER2 + characterization. An automated whole-breast segmentation and feature-extraction workflow, without manual lesion-centered delineation, was applied to the breast region to capture broader parenchymal and microenvironmental texture patterns while reducing dependence on manual lesion annotation. Intensity-based, first-order, and second-order texture features were extracted from DICOM mammograms, followed by pairwise statistical testing, false discovery rate correction, effect-size assessment, Gaussian distribution analysis, normalized feature visualization, univariate AUC analysis, and classifier evaluation using logistic regression and linear support vector machines. First-order and intensity-based descriptors showed limited subtype-specific value, whereas second-order texture features provided more informative discriminatory patterns. Among the evaluated feature families, GLCM and NGLDM descriptors showed the most coherent evidence across statistical, visual, and classifier-based analyses, with NGLDM yielding the broadest set of statistically significant features. Classification performance was strongest and most balanced for HER2 + versus healthy controls, while discrimination between HER2 + and other malignant molecular subtypes was modest, context-dependent, and affected by sensitivity-specificity imbalance in several models. Therefore, the present findings more strongly support sensitivity to malignancy-related whole-breast texture alterations than reliable HER2-specific classification among malignant subtypes. Whole-breast mammographic radiomics should be interpreted as an exploratory and complementary source of candidate imaging biomarkers for future validation.
Nowadays, food trends are heading towards gluten-free and healthier food, including cookies, due to the rising prevalence of celiac disease and other gluten-related disorders. One way to keep up with the trend is to use agrowaste flour. However, consumers' acceptance of such cookies may be lower compared to that of cookies made with conventional wheat flour. To enhance both the sensory quality and nutritional value, food additives such as lecithin and low-glycemic sweeteners can be incorporated. Lecithin improves the texture and appearance of crispy cookies, while low-glycemic sweeteners help reduce the glycemic index and glycemic load without compromising consumer preference. The objective of this study was to evaluate and optimize the physical characteristics, sensory attributes, proximate composition, glycemic index, and glycemic load of crispy cookies formulated with durian and papaya seed flours, lecithin, and low-glycemic sweeteners. The research was conducted in two stages: (1) improving texture by determining the optimal concentration of lecithin and (2) replacing refined sugar with an optimal combination of low-glycemic sweeteners such as erythritol, xylitol, and stevia. The optimal concentration of lecithin was found to be 0.5%, while the most effective sweetener formulation based on the De Garmo effectiveness index consisted of 28.10% erythritol and 0.02% stevia. The resulting crispy cookies exhibited improved texture and appearance, a low glycemic index (32.55), and a low glycemic load (4.64), while maintaining good consumer acceptance. These findings highlight the potential of this formulation to be developed further as a functional cookie product suitable for health-conscious consumers.
Sweet potato (Ipomoea batatas (L.) Lam) is a widely cultivated crop valued for its nutritional and functional properties. In Japan, consumers particularly prioritize the sweetness and texture of baked sweet potatoes. Among the free sugars in cooked sweet potatoes, maltose is predominant, generated by β-amylase-mediated hydrolysis of gelatinized starch during heating. This study investigated the relationship between starch gelatinization properties and β-amylase activity in ten soggy-type sweet potato cultivars (Aikomachi, Annouimo, Beniharuka, Benimasari, Fukumurasaki, Himeayaka, Karayutaka, Kenroku, Silksweet, and Tamayutaka) and one intermediate-type standard cultivar (Kokei 14), all cultivated in the same farm. We evaluated free sugar content, starch gelatinization characteristics, amylopectin chain-length distribution, and β-amylase activity. A positive correlation was observed between the proportion of DP13-24 chains in amylopectin and the onset (T o) and peak (T p) gelatinization temperatures, as measured by differential scanning calorimetry (DSC). Himeayaka, with the highest maltose content, also showed the highest β-amylase activity. In contrast, Silksweet had similar enzyme activity but lower maltose levels. These findings indicate that starch gelatinization behavior is key to the sweetness and texture of cooked sweet potatoes. Principal component analysis grouped the cultivars into three categories: typical soggy-type, slightly soggy-type, and near intermediate-type. These insights can guide the breeding and selection of cultivars aligned with consumer preferences.
This study investigates the use of oleogels structured with monoglyceride (MG) and beeswax (BW) as solid fat replacers in filling creams. Six oleogels were fabricated using various ratios of sunflower and camelina oils. The oleogels were evaluated for oil-binding capacity (OBC), thermal, and morphological properties. The best formulations (50SO-50CO-MGO and 50SO-50CO-BWO) were incorporated into the cream formulation at various shortening replacement levels (25%-75%). The results indicated that oleogels containing BW exhibited higher OBC and thermal stability, while MG-based oleogels demonstrated improved rheological strength and desirable texture. Increasing the oleogel concentration promoted a softer, less adhesive texture. In addition, formulated oleogel creams significantly reduced saturated fat content, achieved a more balanced n-6/n-3 ratio, and provided a healthier lipid composition.
Community awareness of swallowing and dysphagia plays a significant role in improving early-referral behavior. Literature reports that community awareness of swallowing and dysphagia in the Western countries to be low. Conversely, India has a diverse cultural, linguistic and healthcare-related factors which may influence the health-seeking behavior and early-referral of dysphagia. Hence, it becomes difficult to generalize the findings of existing literature. The primary objective of this study was to analyze the knowledge, attitudes and practices (KAP) related to swallowing and dysphagia among the community dwelling adults of South India. The secondary objective was to evaluate if age, sex and education levels were associated with these factors. Community dwelling adults were recruited from Mangalore city, India for a cross-sectional survey using a convenience sampling design. A purposive built content validated 27-item questionnaire was distributed using Google Form and/or hard copies to the participants for data collection. Participant's responses were independently analyzed by two Speech Language Pathologists using open content analysis. The responses were summarized as percentages and categories and chi square test was administered to examine the association between age, sex and education levels and KAP enquiries at 0.05 level. A total of 372 participants aged 20-79 years (mean age = 46.26; SD = 15.63) participated in the study. Participants demonstrated limited knowledge of signs, causes, complications and professional management of dysphagia. Aspiration was widely recognized as unsafe, yet only one-tenth correctly identified pneumonia as a complication of dysphagia. Less than one-fifth knew the treatment options for dysphagia. Attitudes reflected fear of choking, discomfort towards nasogastric-tube feeding and moderate willingness to seek help from healthcare professionals. Practices suggested low awareness of Heimlich maneuver, inconsistent food-texture modification and reliance on water to manage dry mouth. Age, sex and education levels were significantly associated with knowledge (saliva is important for chewing, avoid eating in public space to overcome stigma, early intervention helps regain swallowing abilities, age range frequently associated with dysphagia), attitude (fear of choking, preference to non-oral feeds), practices (using internet to find solutions for dysphagia, drinking water before meals or moistening food using water, changing food consistencies, using straw over cup) at p > 0.05 level. Community dwellers demonstrated insufficient knowledge, predominantly negative attitudes and unsafe self-management practices related to swallowing and dysphagia. Strengthened public education, early-referral pathways and inclusion of basic life-support skills are highly warranted to improve community awareness on swallowing and dysphagia. What is already known on this subject Community awareness of dysphagia is low in Western countries. Cultural beliefs, literacy, superstition and access to healthcare influence what people know, how they respond and when they seek help. Understanding knowledge, attitude and practices (KAP) of swallowing and dysphagia in India is critical for reducing self-management risks and improving early-referral behavior. What this study adds to existing knowledge The study provides the first structured KAP analysis on swallowing and dysphagia in an Indian community . Participants recognized aspiration as dangerous, yet lacked awareness of critical signs, causes, treatment options and responsible team members. Fear of choking was high, and most were uncomfortable with tube-based feeding. The public seldom employed safe compensatory strategies and very few were familiar with Heimlich maneuver or food-texture modification. Age, sex and education levels were significantly associated with multiple KAP variables. What are the clinical implications of this work? There is an urgent need to conduct more public awareness programs on prevention, early identification and intervention of dysphagia by healthcare professionals involved in dysphagia care. Efforts must be scaled to provide basic life support (BLS) skills training programs, including training in Heimlich maneuver, to the public.
Freezing and thawing significantly affect the texture and flavor of glutinous rice-based desserts like Daifuku. This study investigated the impact of magnetic field-assisted thawing (MFT) on Daifuku quality, comparing it with conventional refrigerated thawing (RFT) under identical freezing conditions. Daifuku samples were frozen at -20 °C in a pulsed magnetic field (6 mT, 0.8 Hz) and thawed at 5 °C under various MFT conditions (static and pulsed fields). Results showed that MFT, particularly at 4 mT and 0.6 Hz, shortened thawing time by 18.6%, preserved texture and aroma. MFT inhibited ice recrystallization, maintained starch-protein network integrity, improved water distribution by limiting bound water migration and promoted uniform pore distribution. Compared to RFT, MFT-treated samples exhibited 80% reduced chewiness, 18% increased resilience and improved viscoelastic properties. Sensory evaluation revealed that MFT-treated samples resembled fresh Daifuku. These findings confirm MFT as an effective and economical thawing strategy for glutinous rice products.
In atomic solids, annealing transforms disordered structures into ordered crystals through thermal activation, whereas realizing a comparable process in quasiparticle lattices is highly desirable. Magnetic skyrmions are topological spin textures that can form ordered lattice and undergo equilibrium phase transitions, yet thermal activation is insufficient to overcome their kinetic constraints or provide tunable control. Here, we demonstrate field-driven annealing of skyrmions in two-dimensional van der Waals Fe3GaTe2 (FGaT) at room temperature. Oscillating magnetic fields drive the formation of polycrystalline skyrmion lattices, whereas bipolar current pulses generate anisotropic hexatic states through current-induced lattice distortion. Despite distinct external fields, both processes follow similar defect-mediated crystallization dynamics. The annealing is enabled by the interplay between DMI and MA, while the thermodynamics are primarily governed by dipolar interactions. Our findings demonstrate a pathway for annealing control of topological spin textures and establish FGaT as a platform for exploring skyrmion collective behaviour and reconfigurable spintronics.
The global poultry industry has experienced rapid growth, driven by consumer demand for affordable, high-quality protein. However, this progress has been accompanied by the emergence of growth-related myopathies, notably Spaghetti Meat (SM) and the more recently described Gaping, which compromise meat quality, yield, and marketability. SM, first reported in 2015, is characterized by the detachment and weakening of Pectoralis major fibers, resulting in a stringy, mushy texture of the meat. Gaping, affecting the Pectoralis minor, presents as separations between fiber bundles and tendon tears. Incidence rates of SM vary widely, from 10% to over 36%, while gaping prevalence remains inconsistently reported. Detection traditionally relies on visual scoring, but novel approaches, such as bioelectrical impedance, automated imaging, and spectroscopy, are under investigation to enable early identification. Histological analyses reveal shared features of muscle degeneration, fibrosis, lipid infiltration, and altered collagen structure, with oxidative stress and impaired regeneration implicated in both myopathies. Multiple factors contribute, including genetics, muscle hypertrophy, nutrition, environment, and processing conditions. Notably, delayed chilling, aggressive defeathering, immersion water chilling, and mechanical breast filleting increase SM severity, while dietary antioxidants and trace minerals can sometimes mitigate occurrence. SM and gaping affect technological quality by reducing textural integrity, protein solubility, and water-holding capacity, although their impacts are less severe than wooden breast or white striping. Current mitigation strategies focus on selective breeding, optimized nutrition, and modified processing parameters, but the complexity of these myopathies underscores the need for integrated approaches. Future research should prioritize in short term, the non-genetic strategies, including improvements in processing, nutrition, and management, while in the long term, the genetic basis of this myopathy, particularly the coexistence of affected and unaffected birds within the same population, to support balanced breeding strategies that preserve meat quality and consumer acceptance.
Timely harvesting of fresh tomatoes is urgently needed. To address this issue, this study proposes DDC-YOLOv11n, a model suitable for real-time detection of tomato ripeness in complex greenhouse environments. A Zero-DCE adaptive enhancement module is first deployed at the input stage to restore and enhance the true color and texture details of the images. An improved Deep Residual Shrinkage Network (DRSN) is then added to YOLOv11n to perform adaptive soft-threshold filtering on feature maps, reducing the interference of image noise on the detection targets. Finally, the CBAM spatial attention is enhanced through dilated convolution and channel grouping to form the LKCBAM module, which expands the equivalent receptive field while controlling the increase in parameters, thereby improving tomato detection accuracy in occluded and dense scenes. Experimental results show that the DDC-YOLOv11n model achieves the best recognition performance: compared with the original YOLOv11n, its mAP@0.5, precision, recall, and F1 score are increased by 16.8%, 24.6%, 8.3%, and 18.1%, respectively. These findings facilitate real-time tomato ripeness detection in complex greenhouse environments and provide perceptual information for subsequent management tasks such as harvesting.
This study developed a chitosan (CS)/dialdehyde carboxymethyl cellulose (DCMC) composite film loaded with perillaldehyde (PAE) and evaluated its functional properties and application in cheese preservation. FTIR analysis suggested successful oxidation of carboxymethyl cellulose (CMC) and possible intermolecular interactions between DCMC and CS. PAE incorporation altered film behaviour in a concentration-dependent manner, with the 3 mg/mL film showing the best balance of transparency, flexibility, and structural uniformity. PAE exhibited strong inhibitory effects against Staphylococcus aureus at all tested levels and Listeria monocytogenes at ≥2 mg/mL. When applied to cheese, the P/DC-CS film reduced texture deterioration, limited colour changes, and significantly slowed lipid oxidation during refrigerated storage. These findings indicate that combining DCMC crosslinking with PAE incorporation offers a feasible approach to produce natural active films suitable for short-term dairy preservation.
Pair density modulation is a phenomenon recently observed in exfoliated flakes of iron-based superconductors, in which the superconducting gap oscillates strongly with the same periodicity as the underlying crystalline lattice. We propose a model that explains this modulation in systems with broken intra-unit-cell symmetries through the emergence of nematic superconductivity, which further breaks the four-fold rotation symmetry. This results in a sublattice texture on the Fermi surface, aligned with the anisotropic superconducting gap of the nematic s± + d state. This gives rise to distinctive gap maxima and minima located on the two inequivalent iron sublattices while still being a zero-momentum pairing state. We discuss how further investigation of such modulations can give insight into the nature of the superconducting pairing, such as the signs of the order parameters and visualization of a phase transition to a mixed two-component state using local probes.
Pain represents a critical vital sign monitored in intensive care unit (ICU) patients. The facial action coding system (FACS) defines facial action units (AUs) and provides a structured framework for pain recognition. Currently, the most broadly used pain assessment method is the pain intensity scale developed by Prkachin and Solomon (PSPI), which relies on predefined AUs to quantify facial expressions. However, due to the influence of underlying diseases and facial texture variations in ICU patients, AUs can fail to transfer to clinical settings accurately. To address this problem, this study uses video sequences of pain states collected from 61 ICU patients under resting, daily, and procedural conditions by using an advanced AU detection system. By evaluating the AUs with statistical features and various classification models, this study identifies six key AUs that outperform the PSPI's predefined AUs in terms of accuracy, precision, recall, and F1-score metrics. Further, this study explores the performance of various temporal self-learning networks in the pain assessment task, thus further validating the effectiveness of the identified AU combination. The results presented in this study demonstrate that using AU dynamic learning in combination with deep temporal analysis can improve the reliability of clinical pain assessment. Finally, this study offers a promising approach for automated pain monitoring systems in ICU settings.
Post-burn auricular defects compromise both aesthetics and facial symmetry, often imposing significant social and psychological burdens that severely diminish patients' quality of life. Scarring in the mastoid region following burns typically exhibits poor elasticity and texture, along with compromised cutaneous blood supply. Scar contracture further leads to displacement and deformation. These factors collectively contribute to the considerable complexity and variability inherent in post-burn auricular reconstruction. The intricate three-dimensional structure of the auricle itself renders its restoration a formidable challenge in plastic and reconstructive surgery. In this study, we present a single-stage reconstruction strategy for post-burn ear deformity applicable when local skin is unsuitable and the ipsilateral temporoparietal fascia is non-viable. The technique involves framework fabrication using autologous costal cartilage, followed by coverage with a contralateral free temporoparietal fascial flap. We propose that this approach offers a valuable and effective option for auricular reconstruction in such complex scenarios.